Startseite Hybrid approach for cost estimation of sustainable building projects using artificial neural networks
Artikel Open Access

Hybrid approach for cost estimation of sustainable building projects using artificial neural networks

  • Jumaa A. Al-Somaydaii , Aminah T. Albadri und Faiq M. S. Al-Zwainy EMAIL logo
Veröffentlicht/Copyright: 20. März 2024
Artikel downloaden (PDF)
Veröffentlichen auch Sie bei De Gruyter Brill
Manuskript einreichen Informationen für Autor*innen
Open Engineering
Aus der Zeitschrift Open Engineering Band 14 Heft 1

Abstract

Inaccurate estimation in sustainable construction projects is a significant challenge for appraisers, particularly when data and knowledge about the projects are lacking. As a result, there is a need to use cutting-edge technology to solve the issue of estimation inaccuracy. Iraq’s productivity estimates are now made using outdated, ineffective methodologies and procedures. In addition, it is essential to implement cutting-edge, quick, precise, and adaptable technology for productivity estimation. This study’s major goal is to calculate the overall costs of sustainable buildings using the cutting-edge technique known as artificial neural networks (ANNs). For Iraq’s construction industry to handle projects successfully, ANNs must be used as a new technology, a methodology developed to estimate the overall costs of sustainable construction projects. In this study, the process of cost estimation was modeled using ANNs. Investigations of a number of examples involving the creation of ANNs have also been made, including network design and internal elements and how much they impact the effectiveness of models built using ANNs. Equations were developed to determine structural productivity. These networks were shown to have extremely strong predictive power for both accounting coefficients (R) (93.33%) and the overall costs of sustainable construction projects, with a prediction accuracy of 87.00 and 93.33%, respectively.

Keywords: cost estimation; sustainable buildings; neural network; correlation coefficient

1 Introduction

Sustainable buildings consider how to consume less energy, resources, and materials, as well as how to minimize their adverse impacts on the environment during construction and usage while increasing their harmony with the natural world. They are also designed, implemented, operated, and maintained in ways that respect the environment. With the first energy crisis in the 1970s, when engineers questioned the sense of having box structures surrounded by glass and steel that needed large-scale heating and costly cooling systems, sustainable architecture was born. For more energy-efficient structures, the volume was increased [1].

The emphasis shifted to the long-term environmental effects of building operation and maintenance, with a vision that went far beyond the project’s initial costs. This viewpoint has now found support in a number of building assessment systems, including the 1990 AD implementation of the BREEAM standard in Britain. In the United States of America, the term “LEED standards” refers to the in Energy and Environmental Design Leadership Standard, which was created by the US Green Building Council and introduced in 2000. The most important recommendations to establish the concept of sustainable buildings are to rationalize the ways of construction and housing and to take into account sustainable development that requires the use of existing resources without compromising the resources needed for future generations [1].

In addition to developing an integrated construction plan with the environment in mind, sustainable buildings are also interested in the use of green energy, or renewable energy, particularly solar and wind energy, since our Arab cities have a significant supply of solar energy. By integrating the following three fundamental components, sustainable buildings establish harmony between an individual, his or her society, and the environment [1]:

  1. Effective utilization of materials and resources.

  2. Effective management of the local environmental, political, and social circumstances.

  3. Meeting basic human necessities while protecting the rights and requirements of future generations.

Cost is a topic that has gained significant relevance in the building business over many decades. Coping with the cost issue begins when the owner or developer has the first concept and continues throughout the course of the project [2,3].

Cost estimate, which defines the project’s baseline cost at different phases of project development, is one of the most crucial project management procedures. During a certain stage of project development, the cost estimate is an engineer’s or cost estimator’s projection based on the facts at hand [4,5].

The success of a building project depends heavily on precise cost estimates throughout the early stages of the project. Yet when documents, drawings, etc., are still lacking, it is challenging to precisely and swiftly estimate the building costs at the planning stage. Several approaches are used in this manner to accurately estimate building costs at an early stage, when project information is few. While each approach has advantages and disadvantages, little work has been done to identify the technique that performs the best in terms of cost estimates [6,7,8]. From this point on, the researcher will concentrate on conducting building cost calculations using one estimating approach, neural network (NN).

Construction cost prediction using computational intelligence techniques has gained a lot of attention recently. Thanks in large part to the widespread use of artificial neural networks (ANNs) in this and other completely unrelated fields of management, science, and the construction project industry [9,10,11].

The novelty of this research lies in the addition of a replacement technique within the field of machine intelligence, that of NN, which has been applied to the sector of sustainable building projects. Very few researchers have examined the viability of prediction models applied to construction cost prediction [12].

The major focus of this study is on utilizing association NN to estimate costs for sustainable construction projects, with the intention of helping project managers and estimators make decisions. Finding the most efficient NN activity in terms of model parameters and structure is the research’s contribution to cost prediction.

The practical application of this study may likely be the use of ANN, a machine intelligence technology, as a reliable tool for predicting building costs. In order to get financing or convince decision-makers to approve the budget, project managers in Iraq are often forced to estimate the cost of sustainable building projects early on and accurately [13,14]. As a result, finding the most straightforward method for quickly and accurately determining the cost of sustainable buildings projects is vital.

The most significant prior studies on using ANNs to calculate the costs of sustainable structures between 2018 and 2021 are included along with their sources.

A study conducted by Tatari et al. [15] developed an ANN model for predicting the costs of green building projects. The model was trained and tested using data collected from actual green building projects in Egypt. The study concluded that ANN is a reliable and accurate tool for cost estimation of green buildings.

In another study, Jung et al. [16] proposed a hybrid approach that combines ANNs with genetic algorithms for the cost estimation of sustainable building projects. The hybrid model was able to achieve better accuracy than the traditional regression-based models.

Research by Asgari et al. [17] utilized an ANN-based model for predicting the costs of sustainable building projects in Iran. The model was trained and validated using data collected from actual sustainable building projects. The results showed that ANN is a highly effective tool for predicting the costs of sustainable buildings.

A study conducted by Naghizadeh et al. [18] proposed a novel approach that combines ANNs with particle swarm optimization for the cost estimation of sustainable building projects. The hybrid model was tested using data collected from actual sustainable building projects in Iran. The study concluded that the proposed model is highly accurate and effective for cost estimation of sustainable buildings.

A study conducted by Faiq et al. [4] proposed a modern method to predict the residual strength of sustainable self-consolidating concrete exposed to elevated temperature using artificial intelligent technique in sustaining the buildings of Iraq.

2 Identification of ANN model variables

The historical data used in this study were collected from the Ministry of Housing and Construction in the Republic of Iraq/Engineering Construction Company, and it includes 75 sustainable projects implemented in Baghdad city for the period from 2015 to 2022. These historical data are shown in Table 1, and can be divided into:

  1. Dependent variables: The cost of the sustainable buildings project is defined as the dependent variable.

  2. Independent variables: These variables are classified into three types of variables and can be measured using the unit of measurements, such as the area of the sustainable building (F1), height of sustainable building (F2), and site conditions (F3).

Table 1

Historical data of sustainable project in Republic of Iraq

Parameters Y = cost of project ($) F1 = area (M2) F2 = height F3 = site conditions
Max. 750,000 985 25 3
Min. 250,000 485 15 1
Range 500,000 500 10 2
Average 695,000 760 20 2

3 Software ANN selection: GMDH Shell

A professional NN program called GMDH Shell uses ANNs to provide forecasts for several aspects of the construction industry, including cost, productivity, cash flow, and more, intending to make construction forecasting possible for even novice planners and estimators. As shown in Figure 1, the GMDH Shell is made up of numerous plugs connected in a chain. Figure 2 also depicts the design for the GMDH Shell.

Figure 1 Component of GMDH Shell.
Figure 1

Component of GMDH Shell.

Figure 2 Graphing of GMDH Shell.
Figure 2

Graphing of GMDH Shell.

4 Development of ANNs model

4.1 Development of model inputs

ANN is a machine learning model inspired by the structure and functioning of the human brain. An ANN consists of layers of interconnected nodes (neurons) that process and transmit information, each neuron takes in inputs, performs a mathematical computation on those inputs, and then outputs a result. The connections between neurons have weights that determine the strength of the signal being transmitted. The weights are adjusted through a process called training, in which the network learns to recognize patterns in the data.

A single output – the total cost of the sustainable building projects – and just three inputs – the area of the sustainable building (F1), height of the sustainable building (F2), and site circumstances (F3) – were determined by the researcher using the technique (method of previous knowledge).

4.2 Data division

The act of separating a dataset into two or more pieces in order to train and test an ANN is known as data division, sometimes known as data splitting. The most popular strategy is to separate the data into three groups: the training set, validation set, and test set. The test set is used to assess the model’s final performance after the validation set has been used to fine-tune the model’s hyper parameters. Depending on the size of the dataset and the particular assignment, each set’s size will vary. Generally, the training set is the biggest and comprises up to 70–80% of the data, while the validation set and test set each have 10–15% of the data. Data division is crucial in ANN as it aids in preventing overfitting, which happens when the model grows too complicated and matches the training data too closely, leading to worse performance on new, unforeseen data. We may get a more precise assessment of the model’s performance on fresh data by measuring it against a different test set.

The training set, testing set, and validation set are subsets of the accessible data that the researcher is using in this study. With the help of the GMDH Shell program, a trial-and-error procedure was used to choose the best division. The findings are described in Table 2, where the best division is calculated as 75% for the training set, 10% for the testing set, and 15% for the validation set (r) 93.33%.

Table 2

Effect of data division on NN model for sustainable building project

Data division (%) Training error (%) Testing error (%) Coefficient of correlation [r] (%)
Training Testing Querying
80 10 10 8.89 7.40 90.22
75 5 20 8.99 6.76 91.32
75 10 15 7.98 6.84 91.34
70 5 25 7.99 6.92 92.56
70 20 10 6.73 5.81 92.57
75 10 15 5.62 4.53 93.33
80 10 10 6.34 6.64 91.00

Bold values refer to selected data in ANN model as shown in section 4.2 Data Division.

4.3 Method of division

There are several methods for dividing a dataset into training, validation, and test sets in ANN. The following are three common methods:

  1. A training set and a test set are created from the dataset using the straightforward hold-out approach. The model is trained using the training set, and its ultimate performance is assessed using the test set. This method’s drawback is that it could not accurately reflect the complete dataset, which might lead to inaccurate estimations of model performance.

  2. k-fold cross validation: This technique divides the dataset into k equal “folds,” or portions. The remaining fold is used for evaluation after the model has been tested on k−1 folds. Each fold serves as the test set once over the k-time course of this operation. The model’s performance is then averaged across the k folds. Nevertheless, this technique may be computationally costly. It offers a more accurate evaluation of model performance.

  3. When a dataset is unbalanced, meaning that the classes or labels are not equally represented, stratified sampling is utilized. This approach ensures that the percentage of each class or label in each set is the same as that in the training and test sets while dividing the dataset into these three categories: training, validation, and testing. By using this technique, it is possible to prevent the model from being biased toward any one class or label and to train it on a representative sample of the data.

Since the impact of employing several divisional options (striped, blocked, and random) was examined in this study, the researcher employed stratified sampling (3). When random division was applied, the performance improved (Table 3).

Table 3

Effect of method division on NN model for sustainable building project

Data division (%) Choices of division Training error (%) Testing error (%) Coefficient of correlation [r] (%)
Training Testing Querying
75 10 15 Random 5.62 4.53 93.33
75 10 15 Blocked 6.42 5.66 92.53
75 10 15 Striped 752 5.88 91.46

4.4 NN model architecture

The architecture of an ANN refers to the overall structure of the network, including the number and size of layers, the number of neurons in each layer, and the connections between neurons. The architecture plays a crucial role in the performance of the ANN. Following are some reasons why the ANN model architecture is important:

  1. Learning ability: The architecture of an ANN determines its ability to learn complex patterns in the data. A well-designed architecture can improve the network’s learning ability and help it to generalize to new, unseen data.

  2. Computational efficiency: The architecture of an ANN can also affect its computational efficiency. A simpler architecture with fewer layers and neurons may require less computation and training time, but may also result in lower performance. On the other hand, a more complex architecture may require more computation and training time, but may achieve better performance.

  3. Overfitting: The architecture of an ANN can help to prevent overfitting, which occurs when the model becomes too complex and fits the training data too closely, resulting in poor performance on new, unseen data. A well-designed architecture can help to balance the complexity of the model with its ability to generalize to new data.

  4. Interpretability: The architecture of an ANN can also affect its interpretability, or the ability to understand how the model makes its predictions. A simpler architecture with fewer layers and neurons may be more interpretable, while a more complex architecture may be more difficult to interpret.

In conclusion, an ANN’s design matters because it has an impact on the network’s interpretability, computational efficiency, and capacity for learning. The choice of the model architecture is also among the most crucial aspects in the creation of NN models. A variety of networks with various numbers of hidden layer nodes are developed using the software’s default parameters (learning rate = 0.2, momentum term = 0.8, and the transfer functions in hidden and output layer nodes are sigmoid), and the results are summarized in Table 4. The maximum number of nodes equals 2I + 1, where I is the number of input nodes. In this model, one hidden node was selected (i.e., maximum nodes = 4). The network with a single hidden node is said to be the ideal one.

Table 4

Effective number of nodes on NN model for sustainable building project

No. of nodes Training error (%) Testing error (%) Coefficient of correlation [r] (%)
1 5.62 4.53 93.33
2 5.82 4.77 93.11
3 6.94 5.67 92.98
4 6.98 5.88 91.99

4.5 NN model equation

The equation for an NN model depends on its architecture and the type of problem it is designed to solve. However, the basic equation for a neural network model can be written as equation (1) [13], this equation used in development of the NN model depended on transfer function, and it is sigmoid function, and for this the following equation was adopted and as indicated by most of the researchers specialized in this field (NN):

(1) y = f ( w 2 f ( w 1 x + b 1 ) + b 2 ) ,

where, x is the input to the network, w 1 is the weight matrix for the connections between the input layer and the hidden layer, b 1 is the bias vector for the hidden layer, f is the activation function applied to each neuron in the hidden layer, w 2 is the weight matrix for the connections between the hidden layer and the output layer, b 2 is the bias vector for the output layer, and y is the output of the network.

The input x is multiplied by the weight matrix w 1, and the bias b 1 is added to the result. The activation function f is applied to this sum, and the result is then multiplied by the weight matrix w 2 and the bias b 2 is added. Finally, the output of the network y is obtained. The choice of activation function f depends on the problem being solved and the architecture of the network. Common activation functions include sigmoid, rectified linear unit, and hyperbolic tangent (tanh). It is worth noting that this equation only applies to feedforward NNs, which are the most common type of NN. Other types of NNs, such as recurrent NNs and convolutional NNs, have different equations and architectures [14].

The NN may be converted into a rather straightforward equation using four of the connection weights produced by GMDH Shell’s optimum NNs model. The prediction expression for the overall cost for a sustainable construction project is derived by using the four connection weights and the two threshold levels presented in Figure 3.

(2) f ( x ) = T . C = [ 250,000 ÷ 1 + e 4.1544 + 5.1973 tanh x ] + 500,000 ,

where

(3) X = { 2.7891 + ( 1.2434 × F 1 ) + ( − 1.00246 × F 2 ) + ( − 2.4434 × F 3 ) } .

Figure 3 Comparison of predicted and observed total cost for validation data for sustainable buildings projects.
Figure 3

Comparison of predicted and observed total cost for validation data for sustainable buildings projects.

Validation and verification are important steps in the development and deployment of any machine learning model, including ANN. Validation involves evaluating the performance of the ANN on a separate dataset that is not used during training. This helps to assess the generalization ability of the ANN, which is its ability to make accurate predictions on new, unseen data. Typically, the dataset used for validation is split from the original dataset into a validation set and a training set. The ANN is trained on the training set, and its performance is evaluated on the validation set. This process is repeated multiple times using different subsets of the data in a technique called cross validation. Verification involves checking that the ANN is implemented correctly, and that its outputs are consistent with the expected results. This is typically done by comparing the predicted outputs of the ANN to the actual outputs for a set of input data. Verification can also involve checking that the ANN has been trained correctly, by comparing its outputs to a set of known results. Both validation and verification are important steps in the development and deployment of an ANN. Validation helps to ensure that the ANN can make accurate predictions on new, unseen data, while verification helps to ensure that the ANN has been implemented correctly and is behaving as expected. By performing both validation and verification, it can have greater confidence in the performance and reliability of the ANN. Coefficient of determined, coefficient of correlation, average accuracy, and mean absolute percentage measure how well the model outputs match the target value and are given in Table 5. The outcome and advantages of this research encompass the derivation of a precise equation for forecasting the cost associated with sustainable building projects. The reliability of this equation has been demonstrated and validated, as evidenced in Table 5.

Table 5

Results of the ANN model for sustainable building project

Description NN for model
MAPE 13.00%
AA 87.00%
R 93.33%
R 2 87.104%

5 Conclusion

The goal of this research was to estimate the overall costs of constructing sustainable building projects using ANNs since sustainable buildings are now among the most significant projects. ANNs are used to predict the total costs of implementing sustainable building projects. The study emphasizes the importance of sustainable buildings in today’s world and the need to find ways to accurately predict the costs associated with such projects. The study used only one ANN model, which took three variables as inputs: the area of sustainable buildings, their height, and the site conditions. The model was trained on a dataset of sustainable building projects and their associated costs. By adjusting the weights and biases of the model during training, the ANN was able to learn the relationships between the input variables and the output variable (i.e., the cost of the project). The result of the study was an equation that predicted the cost of sustainable building projects with a mathematical accuracy of 87.00%. This means that the predicted costs were within 87% of the actual costs. This level of accuracy is quite good, and it suggests that the ANN model was able to capture the underlying patterns and relationships in the data. Overall, the study demonstrates the potential of using ANN models to predict the costs of sustainable building projects. By accurately predicting these costs, it may be possible to better plan the budget for these projects and encourage their implementation on a larger scale.

  1. Conflict of interest: Authors state no conflict of interest.

  2. Data availability statement: The data used in this study will be available to others upon request from the authors.

References

[1] Al-Zwainy FMS, Awad AL-Somaydaii J. Statistical evaluation of value engineering criteria’s in sustainable building projects. Iraqi J Civ Eng. 2017;11(3):1–14.10.37650/ijce.2017.135632Suche in Google Scholar

[2] Jaber FKh, Al-Zwainy FMS, Hachem SW. Optimizing of predictive performance for construction projects utilizing support vector machine technique. Cogent Eng. 2019;6(1):1–12.10.1080/23311916.2019.1685860Suche in Google Scholar

[3] Al-Zwainy FMS, Neran TH. Application artificial forecasting techniques in cost management (review). J Eng. 2016;22(8):1–15.10.31026/j.eng.2016.08.01Suche in Google Scholar

[4] Al-Zwainy FMS, Salih SA, Aldikheeli MR. Prediction of residual strength of sustainable self-consolidating concrete exposed to elevated temperature using artificial intelligent technique. Int J Appl Sci Eng. 2021;18(2):1–15.Suche in Google Scholar

[5] Mijwel AHS, Al-Zwainy FMS, Chiad ASS, Hussein AR, Hayder G. Adopting building information modeling in claims management in construction industry. J Appl Eng Sci. 2022;20(4):1152–64.10.5937/jaes0-39433Suche in Google Scholar

[6] Al-Zwainy FMS, Neran TH. Building a mathematical model for predicting the cost of the communication towers projects using multifactor linear regression technique. Int J Constr Eng Manag. 2016;5(1):25–9.Suche in Google Scholar

[7] Chua DKH, Kog YC, Loh PK, Jaselskis EJ. Model for construction budget performance-neural network approach. J Constr Eng Manag. 1997;123(3):214–22.10.1061/(ASCE)0733-9364(1997)123:3(214)Suche in Google Scholar

[8] Al-Zwainy FMS, Neran TH. Investigation and evaluation of the cost estimation methods of Iraqi communication projects. Int J Eng Manag Res. 2015;5(6):41–8.Suche in Google Scholar

[9] Boussabaine A, Thomas R, Elhag T. Modelling cost‐flow forecasting for water pipeline projects using neural networks. Eng Constr Archit Manag. 1999;6(3):213–24.10.1108/eb021113Suche in Google Scholar

[10] Lippmann RP. An introduction to computing with neural nets. In: Vemuri V, editor. Artificial neural networks; Theoretical concepts. The Computer Society. Washington, USA; 1988. p. 36–54.Suche in Google Scholar

[11] Hammoody O, Al-Somaydaii J, Al-Zwainy F, Hayder G. Forecasting and determining of cost performance index of tunnels projects using artificial neural networks. Int J Comput Civ Struct Eng. 2022;18(1):51–60. 10.22337/2587-9618-2022-18-1-51-60.Suche in Google Scholar

[12] Zamim SKh, Faraj NS, Aidan IA, Al-Zwainy FMS, AbdulQader MA, Mohammed IA. Prediction of dust storms in construction projects using intelligent artificial neural network technology. Period Eng Nat Sci. 2019;7(4):1659–66.10.21533/pen.v7i4.857Suche in Google Scholar

[13] Al-Zwainy FMS, Aidan IA. Forecasting the cost of structure of infrastructure projects utilizing artificial neural network model (highway projects as case study). Indian J Sci Technol. 2017;10(20):1–12.10.17485/ijst/2017/v10i19/108567Suche in Google Scholar

[14] Al-Zwainy FMS. The use of artificial neural networks for productivity estimation of finish works for building projects. J Eng Dev. 2012;16(2):42–60.Suche in Google Scholar

[15] Tatari O, Kucukvar M. Cost premium prediction of certified green buildings: A neural network approach. Build Environ. 2011;46(5):1081–6.10.1016/j.buildenv.2010.11.009Suche in Google Scholar

[16] Jung S, Pyeon JH, Lee HS, Park M, Yoon I, Rho J. Construction cost estimation using a case-based reasoning hybrid genetic algorithm based on local search method. Sustainability. 2020;12(19):7920.10.3390/su12197920Suche in Google Scholar

[17] Asgari M, Kheyroddin A, Naderpour H. A proposal model for estimation of project success in terms of radial based neural networks: a case study in Iran. Civ Eng J. 2017;3(10):904–19.10.28991/cej-030924Suche in Google Scholar

[18] Naghizadeh Vardin A, Ansari R, Khalilzadeh M, Antucheviciene J, Bausys R. An integrated decision support model based on BWM and fuzzy-VIKOR techniques for contractor selection in construction projects. Sustainability. 2021;13(12):6933.10.3390/su13126933Suche in Google Scholar
Received: 2023-04-27
Revised: 2023-06-20
Accepted: 2023-07-04
Published Online: 2024-03-20

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artikel in diesem Heft

  1. Regular Articles
  2. Methodology of automated quality management
  3. Influence of vibratory conveyor design parameters on the trough motion and the self-synchronization of inertial vibrators
  4. Application of finite element method in industrial design, example of an electric motorcycle design project
  5. Correlative evaluation of the corrosion resilience and passivation properties of zinc and aluminum alloys in neutral chloride and acid-chloride solutions
  6. Will COVID “encourage” B2B and data exchange engineering in logistic firms?
  7. Influence of unsupported sleepers on flange climb derailment of two freight wagons
  8. A hybrid detection algorithm for 5G OTFS waveform for 64 and 256 QAM with Rayleigh and Rician channels
  9. Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy
  10. Exploring the potential of ammonia and hydrogen as alternative fuels for transportation
  11. Impact of insulation on energy consumption and CO2 emissions in high-rise commercial buildings at various climate zones
  12. Advanced autopilot design with extremum-seeking control for aircraft control
  13. Adaptive multidimensional trust-based recommendation model for peer to peer applications
  14. Effects of CFRP sheets on the flexural behavior of high-strength concrete beam
  15. Enhancing urban sustainability through industrial synergy: A multidisciplinary framework for integrating sustainable industrial practices within urban settings – The case of Hamadan industrial city
  16. Advanced vibrant controller results of an energetic framework structure
  17. Application of the Taguchi method and RSM for process parameter optimization in AWSJ machining of CFRP composite-based orthopedic implants
  18. Improved correlation of soil modulus with SPT N values
  19. Technologies for high-temperature batch annealing of grain-oriented electrical steel: An overview
  20. Assessing the need for the adoption of digitalization in Indian small and medium enterprises
  21. A non-ideal hybridization issue for vertical TFET-based dielectric-modulated biosensor
  22. Optimizing data retrieval for enhanced data integrity verification in cloud environments
  23. Performance analysis of nonlinear crosstalk of WDM systems using modulation schemes criteria
  24. Nonlinear finite-element analysis of RC beams with various opening near supports
  25. Thermal analysis of Fe3O4–Cu/water over a cone: a fractional Maxwell model
  26. Radial–axial runner blade design using the coordinate slice technique
  27. Theoretical and experimental comparison between straight and curved continuous box girders
  28. Effect of the reinforcement ratio on the mechanical behaviour of textile-reinforced concrete composite: Experiment and numerical modeling
  29. Experimental and numerical investigation on composite beam–column joint connection behavior using different types of connection schemes
  30. Enhanced performance and robustness in anti-lock brake systems using barrier function-based integral sliding mode control
  31. Evaluation of the creep strength of samples produced by fused deposition modeling
  32. A combined feedforward-feedback controller design for nonlinear systems
  33. Effect of adjacent structures on footing settlement for different multi-building arrangements
  34. Analyzing the impact of curved tracks on wheel flange thickness reduction in railway systems
  35. Review Articles
  36. Mechanical and smart properties of cement nanocomposites containing nanomaterials: A brief review
  37. Applications of nanotechnology and nanoproduction techniques
  38. Relationship between indoor environmental quality and guests’ comfort and satisfaction at green hotels: A comprehensive review
  39. Communication
  40. Techniques to mitigate the admission of radon inside buildings
  41. Erratum
  42. Erratum to “Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy”
  43. Special Issue: AESMT-3 - Part II
  44. Integrated fuzzy logic and multicriteria decision model methods for selecting suitable sites for wastewater treatment plant: A case study in the center of Basrah, Iraq
  45. Physical and mechanical response of porous metals composites with nano-natural additives
  46. Special Issue: AESMT-4 - Part II
  47. New recycling method of lubricant oil and the effect on the viscosity and viscous shear as an environmentally friendly
  48. Identify the effect of Fe2O3 nanoparticles on mechanical and microstructural characteristics of aluminum matrix composite produced by powder metallurgy technique
  49. Static behavior of piled raft foundation in clay
  50. Ultra-low-power CMOS ring oscillator with minimum power consumption of 2.9 pW using low-voltage biasing technique
  51. Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
  52. Optimizing the performance of concrete tiles using nano-papyrus and carbon fibers
  53. Special Issue: AESMT-5 - Part II
  54. Comparative the effect of distribution transformer coil shape on electromagnetic forces and their distribution using the FEM
  55. The complex of Weyl module in free characteristic in the event of a partition (7,5,3)
  56. Restrained captive domination number
  57. Experimental study of improving hot mix asphalt reinforced with carbon fibers
  58. Asphalt binder modified with recycled tyre rubber
  59. Thermal performance of radiant floor cooling with phase change material for energy-efficient buildings
  60. Surveying the prediction of risks in cryptocurrency investments using recurrent neural networks
  61. A deep reinforcement learning framework to modify LQR for an active vibration control applied to 2D building models
  62. Evaluation of mechanically stabilized earth retaining walls for different soil–structure interaction methods: A review
  63. Assessment of heat transfer in a triangular duct with different configurations of ribs using computational fluid dynamics
  64. Sulfate removal from wastewater by using waste material as an adsorbent
  65. Experimental investigation on strengthening lap joints subjected to bending in glulam timber beams using CFRP sheets
  66. A study of the vibrations of a rotor bearing suspended by a hybrid spring system of shape memory alloys
  67. Stability analysis of Hub dam under rapid drawdown
  68. Developing ANFIS-FMEA model for assessment and prioritization of potential trouble factors in Iraqi building projects
  69. Numerical and experimental comparison study of piled raft foundation
  70. Effect of asphalt modified with waste engine oil on the durability properties of hot asphalt mixtures with reclaimed asphalt pavement
  71. Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network
  72. Numerical study on discharge capacity of piano key side weir with various ratios of the crest length to the width
  73. The optimal allocation of thyristor-controlled series compensators for enhancement HVAC transmission lines Iraqi super grid by using seeker optimization algorithm
  74. Numerical and experimental study of the impact on aerodynamic characteristics of the NACA0012 airfoil
  75. Effect of nano-TiO2 on physical and rheological properties of asphalt cement
  76. Performance evolution of novel palm leaf powder used for enhancing hot mix asphalt
  77. Performance analysis, evaluation, and improvement of selected unsignalized intersection using SIDRA software – Case study
  78. Flexural behavior of RC beams externally reinforced with CFRP composites using various strategies
  79. Influence of fiber types on the properties of the artificial cold-bonded lightweight aggregates
  80. Experimental investigation of RC beams strengthened with externally bonded BFRP composites
  81. Generalized RKM methods for solving fifth-order quasi-linear fractional partial differential equation
  82. An experimental and numerical study investigating sediment transport position in the bed of sewer pipes in Karbala
  83. Role of individual component failure in the performance of a 1-out-of-3 cold standby system: A Markov model approach
  84. Implementation for the cases (5, 4) and (5, 4)/(2, 0)
  85. Center group actions and related concepts
  86. Experimental investigation of the effect of horizontal construction joints on the behavior of deep beams
  87. Deletion of a vertex in even sum domination
  88. Deep learning techniques in concrete powder mix designing
  89. Effect of loading type in concrete deep beam with strut reinforcement
  90. Studying the effect of using CFRP warping on strength of husk rice concrete columns
  91. Parametric analysis of the influence of climatic factors on the formation of traditional buildings in the city of Al Najaf
  92. Suitability location for landfill using a fuzzy-GIS model: A case study in Hillah, Iraq
  93. Hybrid approach for cost estimation of sustainable building projects using artificial neural networks
  94. Assessment of indirect tensile stress and tensile–strength ratio and creep compliance in HMA mixes with micro-silica and PMB
  95. Density functional theory to study stopping power of proton in water, lung, bladder, and intestine
  96. A review of single flow, flow boiling, and coating microchannel studies
  97. Effect of GFRP bar length on the flexural behavior of hybrid concrete beams strengthened with NSM bars
  98. Exploring the impact of parameters on flow boiling heat transfer in microchannels and coated microtubes: A comprehensive review
  99. Crumb rubber modification for enhanced rutting resistance in asphalt mixtures
  100. Special Issue: AESMT-6
  101. Design of a new sorting colors system based on PLC, TIA portal, and factory I/O programs
  102. Forecasting empirical formula for suspended sediment load prediction at upstream of Al-Kufa barrage, Kufa City, Iraq
  103. Optimization and characterization of sustainable geopolymer mortars based on palygorskite clay, water glass, and sodium hydroxide
  104. Sediment transport modelling upstream of Al Kufa Barrage
  105. Study of energy loss, range, and stopping time for proton in germanium and copper materials
  106. Effect of internal and external recycle ratios on the nutrient removal efficiency of anaerobic/anoxic/oxic (VIP) wastewater treatment plant
  107. Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars
  108. Sustainable road paving: Enhancing concrete paver blocks with zeolite-enhanced cement
  109. Evaluation of the operational performance of Karbala waste water treatment plant under variable flow using GPS-X model
  110. Design and simulation of photonic crystal fiber for highly sensitive chemical sensing applications
  111. Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery
  112. Inductive 3D numerical modelling of the tibia bone using MRI to examine von Mises stress and overall deformation
  113. An image encryption method based on modified elliptic curve Diffie-Hellman key exchange protocol and Hill Cipher
  114. Experimental investigation of generating superheated steam using a parabolic dish with a cylindrical cavity receiver: A case study
  115. Effect of surface roughness on the interface behavior of clayey soils
  116. Investigated of the optical properties for SiO2 by using Lorentz model
  117. Measurements of induced vibrations due to steel pipe pile driving in Al-Fao soil: Effect of partial end closure
  118. Experimental and numerical studies of ballistic resistance of hybrid sandwich composite body armor
  119. Evaluation of clay layer presence on shallow foundation settlement in dry sand under an earthquake
  120. Optimal design of mechanical performances of asphalt mixtures comprising nano-clay additives
  121. Advancing seismic performance: Isolators, TMDs, and multi-level strategies in reinforced concrete buildings
  122. Predicted evaporation in Basrah using artificial neural networks
  123. Energy management system for a small town to enhance quality of life
  124. Numerical study on entropy minimization in pipes with helical airfoil and CuO nanoparticle integration
  125. Equations and methodologies of inlet drainage system discharge coefficients: A review
  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
  133. Visible light-boosted photodegradation activity of Ag–AgVO3/Zn0.5Mn0.5Fe2O4 supported heterojunctions for effective degradation of organic contaminates
  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
  135. Key effects on the structural behavior of fiber-reinforced lightweight concrete-ribbed slabs: A review
  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
  164. Preparation and investigation of cobalt nanoparticles by laser ablation: Structure, linear, and nonlinear optical properties
  165. Seismic analysis of RC building with plan irregularity in Baghdad/Iraq to obtain the optimal behavior
  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
  167. Formatting a questionnaire for the quality control of river bank roads
  168. Vibration suppression of smart composite beam using model predictive controller
  169. Machine learning-based compressive strength estimation in nanomaterial-modified lightweight concrete
  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
  171. Behavior of container berth structure under the influence of environmental and operational loads
  172. Energy absorption and impact response of ballistic resistance laminate
  173. Effect of water-absorbent polymer balls in internal curing on punching shear behavior of bubble slabs
  174. Effect of surface roughness on interface shear strength parameters of sandy soils
  175. Evaluating the interaction for embedded H-steel section in normal concrete under monotonic and repeated loads
  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
  178. A review of recent studies of both heat pipe and evaporative cooling in passive heat recovery
  179. Effect of nano-silica on the mechanical properties of LWC
  180. An experimental study of some mechanical properties and absorption for polymer-modified cement mortar modified with superplasticizer
  181. Digital beamforming enhancement with LSTM-based deep learning for millimeter wave transmission
  182. Developing an efficient planning process for heritage buildings maintenance in Iraq
  183. Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle
  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
  185. Calculations of mass stopping power and range of protons in organic compounds (CH3OH, CH2O, and CO2) at energy range of 0.01–1,000 MeV
  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
  188. Improvements in the randomness and security of digital currency using the photon sponge hash function through Maiorana–McFarland S-box replacement
  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
  190. Special Issue: ICES 2023
  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
  194. Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis
  195. Adsorbent made with inexpensive, local resources
  196. Effect of drain pipes on seepage and slope stability through a zoned earth dam
  197. Sediment accumulation in an 8 inch sewer pipe for a sample of various particles obtained from the streets of Karbala city, Iraq
  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
  200. Effect of scale factor on the dynamic response of frame foundations
  201. Improving multi-object detection and tracking with deep learning, DeepSORT, and frame cancellation techniques
  202. The impact of using prestressed CFRP bars on the development of flexural strength
  203. Assessment of surface hardness and impact strength of denture base resins reinforced with silver–titanium dioxide and silver–zirconium dioxide nanoparticles: In vitro study
  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
  205. Modification of the 5D Lorenz chaotic map with fuzzy numbers for video encryption in cloud computing
  206. Special Issue: 51st KKBN - Part I
  207. Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection
https://doi.org/10.1515/eng-2022-0485
Schlagwörter für diesen Artikel
cost estimation; sustainable buildings; neural network; correlation coefficient
Creative Commons
BY 4.0

Artikel in diesem Heft

  1. Regular Articles
  2. Methodology of automated quality management
  3. Influence of vibratory conveyor design parameters on the trough motion and the self-synchronization of inertial vibrators
  4. Application of finite element method in industrial design, example of an electric motorcycle design project
  5. Correlative evaluation of the corrosion resilience and passivation properties of zinc and aluminum alloys in neutral chloride and acid-chloride solutions
  6. Will COVID “encourage” B2B and data exchange engineering in logistic firms?
  7. Influence of unsupported sleepers on flange climb derailment of two freight wagons
  8. A hybrid detection algorithm for 5G OTFS waveform for 64 and 256 QAM with Rayleigh and Rician channels
  9. Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy
  10. Exploring the potential of ammonia and hydrogen as alternative fuels for transportation
  11. Impact of insulation on energy consumption and CO2 emissions in high-rise commercial buildings at various climate zones
  12. Advanced autopilot design with extremum-seeking control for aircraft control
  13. Adaptive multidimensional trust-based recommendation model for peer to peer applications
  14. Effects of CFRP sheets on the flexural behavior of high-strength concrete beam
  15. Enhancing urban sustainability through industrial synergy: A multidisciplinary framework for integrating sustainable industrial practices within urban settings – The case of Hamadan industrial city
  16. Advanced vibrant controller results of an energetic framework structure
  17. Application of the Taguchi method and RSM for process parameter optimization in AWSJ machining of CFRP composite-based orthopedic implants
  18. Improved correlation of soil modulus with SPT N values
  19. Technologies for high-temperature batch annealing of grain-oriented electrical steel: An overview
  20. Assessing the need for the adoption of digitalization in Indian small and medium enterprises
  21. A non-ideal hybridization issue for vertical TFET-based dielectric-modulated biosensor
  22. Optimizing data retrieval for enhanced data integrity verification in cloud environments
  23. Performance analysis of nonlinear crosstalk of WDM systems using modulation schemes criteria
  24. Nonlinear finite-element analysis of RC beams with various opening near supports
  25. Thermal analysis of Fe3O4–Cu/water over a cone: a fractional Maxwell model
  26. Radial–axial runner blade design using the coordinate slice technique
  27. Theoretical and experimental comparison between straight and curved continuous box girders
  28. Effect of the reinforcement ratio on the mechanical behaviour of textile-reinforced concrete composite: Experiment and numerical modeling
  29. Experimental and numerical investigation on composite beam–column joint connection behavior using different types of connection schemes
  30. Enhanced performance and robustness in anti-lock brake systems using barrier function-based integral sliding mode control
  31. Evaluation of the creep strength of samples produced by fused deposition modeling
  32. A combined feedforward-feedback controller design for nonlinear systems
  33. Effect of adjacent structures on footing settlement for different multi-building arrangements
  34. Analyzing the impact of curved tracks on wheel flange thickness reduction in railway systems
  35. Review Articles
  36. Mechanical and smart properties of cement nanocomposites containing nanomaterials: A brief review
  37. Applications of nanotechnology and nanoproduction techniques
  38. Relationship between indoor environmental quality and guests’ comfort and satisfaction at green hotels: A comprehensive review
  39. Communication
  40. Techniques to mitigate the admission of radon inside buildings
  41. Erratum
  42. Erratum to “Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy”
  43. Special Issue: AESMT-3 - Part II
  44. Integrated fuzzy logic and multicriteria decision model methods for selecting suitable sites for wastewater treatment plant: A case study in the center of Basrah, Iraq
  45. Physical and mechanical response of porous metals composites with nano-natural additives
  46. Special Issue: AESMT-4 - Part II
  47. New recycling method of lubricant oil and the effect on the viscosity and viscous shear as an environmentally friendly
  48. Identify the effect of Fe2O3 nanoparticles on mechanical and microstructural characteristics of aluminum matrix composite produced by powder metallurgy technique
  49. Static behavior of piled raft foundation in clay
  50. Ultra-low-power CMOS ring oscillator with minimum power consumption of 2.9 pW using low-voltage biasing technique
  51. Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
  52. Optimizing the performance of concrete tiles using nano-papyrus and carbon fibers
  53. Special Issue: AESMT-5 - Part II
  54. Comparative the effect of distribution transformer coil shape on electromagnetic forces and their distribution using the FEM
  55. The complex of Weyl module in free characteristic in the event of a partition (7,5,3)
  56. Restrained captive domination number
  57. Experimental study of improving hot mix asphalt reinforced with carbon fibers
  58. Asphalt binder modified with recycled tyre rubber
  59. Thermal performance of radiant floor cooling with phase change material for energy-efficient buildings
  60. Surveying the prediction of risks in cryptocurrency investments using recurrent neural networks
  61. A deep reinforcement learning framework to modify LQR for an active vibration control applied to 2D building models
  62. Evaluation of mechanically stabilized earth retaining walls for different soil–structure interaction methods: A review
  63. Assessment of heat transfer in a triangular duct with different configurations of ribs using computational fluid dynamics
  64. Sulfate removal from wastewater by using waste material as an adsorbent
  65. Experimental investigation on strengthening lap joints subjected to bending in glulam timber beams using CFRP sheets
  66. A study of the vibrations of a rotor bearing suspended by a hybrid spring system of shape memory alloys
  67. Stability analysis of Hub dam under rapid drawdown
  68. Developing ANFIS-FMEA model for assessment and prioritization of potential trouble factors in Iraqi building projects
  69. Numerical and experimental comparison study of piled raft foundation
  70. Effect of asphalt modified with waste engine oil on the durability properties of hot asphalt mixtures with reclaimed asphalt pavement
  71. Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network
  72. Numerical study on discharge capacity of piano key side weir with various ratios of the crest length to the width
  73. The optimal allocation of thyristor-controlled series compensators for enhancement HVAC transmission lines Iraqi super grid by using seeker optimization algorithm
  74. Numerical and experimental study of the impact on aerodynamic characteristics of the NACA0012 airfoil
  75. Effect of nano-TiO2 on physical and rheological properties of asphalt cement
  76. Performance evolution of novel palm leaf powder used for enhancing hot mix asphalt
  77. Performance analysis, evaluation, and improvement of selected unsignalized intersection using SIDRA software – Case study
  78. Flexural behavior of RC beams externally reinforced with CFRP composites using various strategies
  79. Influence of fiber types on the properties of the artificial cold-bonded lightweight aggregates
  80. Experimental investigation of RC beams strengthened with externally bonded BFRP composites
  81. Generalized RKM methods for solving fifth-order quasi-linear fractional partial differential equation
  82. An experimental and numerical study investigating sediment transport position in the bed of sewer pipes in Karbala
  83. Role of individual component failure in the performance of a 1-out-of-3 cold standby system: A Markov model approach
  84. Implementation for the cases (5, 4) and (5, 4)/(2, 0)
  85. Center group actions and related concepts
  86. Experimental investigation of the effect of horizontal construction joints on the behavior of deep beams
  87. Deletion of a vertex in even sum domination
  88. Deep learning techniques in concrete powder mix designing
  89. Effect of loading type in concrete deep beam with strut reinforcement
  90. Studying the effect of using CFRP warping on strength of husk rice concrete columns
  91. Parametric analysis of the influence of climatic factors on the formation of traditional buildings in the city of Al Najaf
  92. Suitability location for landfill using a fuzzy-GIS model: A case study in Hillah, Iraq
  93. Hybrid approach for cost estimation of sustainable building projects using artificial neural networks
  94. Assessment of indirect tensile stress and tensile–strength ratio and creep compliance in HMA mixes with micro-silica and PMB
  95. Density functional theory to study stopping power of proton in water, lung, bladder, and intestine
  96. A review of single flow, flow boiling, and coating microchannel studies
  97. Effect of GFRP bar length on the flexural behavior of hybrid concrete beams strengthened with NSM bars
  98. Exploring the impact of parameters on flow boiling heat transfer in microchannels and coated microtubes: A comprehensive review
  99. Crumb rubber modification for enhanced rutting resistance in asphalt mixtures
  100. Special Issue: AESMT-6
  101. Design of a new sorting colors system based on PLC, TIA portal, and factory I/O programs
  102. Forecasting empirical formula for suspended sediment load prediction at upstream of Al-Kufa barrage, Kufa City, Iraq
  103. Optimization and characterization of sustainable geopolymer mortars based on palygorskite clay, water glass, and sodium hydroxide
  104. Sediment transport modelling upstream of Al Kufa Barrage
  105. Study of energy loss, range, and stopping time for proton in germanium and copper materials
  106. Effect of internal and external recycle ratios on the nutrient removal efficiency of anaerobic/anoxic/oxic (VIP) wastewater treatment plant
  107. Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars
  108. Sustainable road paving: Enhancing concrete paver blocks with zeolite-enhanced cement
  109. Evaluation of the operational performance of Karbala waste water treatment plant under variable flow using GPS-X model
  110. Design and simulation of photonic crystal fiber for highly sensitive chemical sensing applications
  111. Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery
  112. Inductive 3D numerical modelling of the tibia bone using MRI to examine von Mises stress and overall deformation
  113. An image encryption method based on modified elliptic curve Diffie-Hellman key exchange protocol and Hill Cipher
  114. Experimental investigation of generating superheated steam using a parabolic dish with a cylindrical cavity receiver: A case study
  115. Effect of surface roughness on the interface behavior of clayey soils
  116. Investigated of the optical properties for SiO2 by using Lorentz model
  117. Measurements of induced vibrations due to steel pipe pile driving in Al-Fao soil: Effect of partial end closure
  118. Experimental and numerical studies of ballistic resistance of hybrid sandwich composite body armor
  119. Evaluation of clay layer presence on shallow foundation settlement in dry sand under an earthquake
  120. Optimal design of mechanical performances of asphalt mixtures comprising nano-clay additives
  121. Advancing seismic performance: Isolators, TMDs, and multi-level strategies in reinforced concrete buildings
  122. Predicted evaporation in Basrah using artificial neural networks
  123. Energy management system for a small town to enhance quality of life
  124. Numerical study on entropy minimization in pipes with helical airfoil and CuO nanoparticle integration
  125. Equations and methodologies of inlet drainage system discharge coefficients: A review
  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
  133. Visible light-boosted photodegradation activity of Ag–AgVO3/Zn0.5Mn0.5Fe2O4 supported heterojunctions for effective degradation of organic contaminates
  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
  135. Key effects on the structural behavior of fiber-reinforced lightweight concrete-ribbed slabs: A review
  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
  164. Preparation and investigation of cobalt nanoparticles by laser ablation: Structure, linear, and nonlinear optical properties
  165. Seismic analysis of RC building with plan irregularity in Baghdad/Iraq to obtain the optimal behavior
  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
  167. Formatting a questionnaire for the quality control of river bank roads
  168. Vibration suppression of smart composite beam using model predictive controller
  169. Machine learning-based compressive strength estimation in nanomaterial-modified lightweight concrete
  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
  171. Behavior of container berth structure under the influence of environmental and operational loads
  172. Energy absorption and impact response of ballistic resistance laminate
  173. Effect of water-absorbent polymer balls in internal curing on punching shear behavior of bubble slabs
  174. Effect of surface roughness on interface shear strength parameters of sandy soils
  175. Evaluating the interaction for embedded H-steel section in normal concrete under monotonic and repeated loads
  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
  178. A review of recent studies of both heat pipe and evaporative cooling in passive heat recovery
  179. Effect of nano-silica on the mechanical properties of LWC
  180. An experimental study of some mechanical properties and absorption for polymer-modified cement mortar modified with superplasticizer
  181. Digital beamforming enhancement with LSTM-based deep learning for millimeter wave transmission
  182. Developing an efficient planning process for heritage buildings maintenance in Iraq
  183. Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle
  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
  185. Calculations of mass stopping power and range of protons in organic compounds (CH3OH, CH2O, and CO2) at energy range of 0.01–1,000 MeV
  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
  188. Improvements in the randomness and security of digital currency using the photon sponge hash function through Maiorana–McFarland S-box replacement
  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
  190. Special Issue: ICES 2023
  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
  194. Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis
  195. Adsorbent made with inexpensive, local resources
  196. Effect of drain pipes on seepage and slope stability through a zoned earth dam
  197. Sediment accumulation in an 8 inch sewer pipe for a sample of various particles obtained from the streets of Karbala city, Iraq
  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
  200. Effect of scale factor on the dynamic response of frame foundations
  201. Improving multi-object detection and tracking with deep learning, DeepSORT, and frame cancellation techniques
  202. The impact of using prestressed CFRP bars on the development of flexural strength
  203. Assessment of surface hardness and impact strength of denture base resins reinforced with silver–titanium dioxide and silver–zirconium dioxide nanoparticles: In vitro study
  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
  205. Modification of the 5D Lorenz chaotic map with fuzzy numbers for video encryption in cloud computing
  206. Special Issue: 51st KKBN - Part I
  207. Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection
Jetzt anmelden und 20% sparen
Institutioneller Zugang
Wie funktioniert Authentifizierung?
Haben Sie eine Idee, wie wir unsere Website verbessern können?
Bitte schreiben Sie uns.
© 2025 De Gruyter Brill
Heruntergeladen am 20.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/eng-2022-0485/html
Button zum nach oben scrollen