Modelling and Optimization of CO2 Absorption in Pneumatic Contactors Using Artificial Neural Networks Developed with Clonal Selection-Based Algorithm
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Petronela Cozma
, Elena Niculina Drăgoi , Ioan Mămăligă , Silvia Curteanu , Walter Wukovits , Anton Friedl und Maria Gavrilescu
Abstract
Our research focuses on the application of airlift contactors (ALRs) for the decontamination of CO2-containing gas streams, such as biogas. To assess the performance of ALRs during CO2 absorption, a complex experimental programme was applied in a laboratory-scale rectangular pneumatic contactor, able to operate either as a bubble column or as an airlift reactor. Using the experimental data, a model based on artificial neural network (ANN) was developed. The algorithm for determining the optimal neural network model and for reactor optimization is clonal selection (CS), belonging to artificial immune system class, which is a new computational intelligence paradigm based on the principles of the vertebrate immune system. To improve its capabilities and the probability for highly suitable models and input combinations, addressing maximum efficiency, a Back-Propagation (BK) algorithm – a supervised learning method based on the delta rule – is used as a local search procedure. It is applied in a greedy manner for the best antibody found in each generation. Since the highest affinity antibodies are cloned in the next generation, the effect of BK on the suitability of the individuals propagates into a large proportion of the population. In parallel with the BK hybridization of the basic CS–ANN combination, a series of normalization procedures are included for improving the overall results provided by the new algorithm called nCS-MBK (normalized Clonal Selection-Multilayer Perceptron Neural Network and Back-Propagation algorithm). The optimization allowed for achieving the optimal reactor configuration, which leads to a maximum amount of CO2 dissolved in water.
Funding statement: Funding: Parts of this work were supported by the grant of the Romanian National Authority for Scientific Research, CNCS – UEFISCDI, project number PN-II-ID-PCE-2011-3-0559, Contract 265/2011 and by the “Partnership in priority areas – PN-II” program, financed by ANCS, CNDI – UEFISCDI, project PN-II-PT-PCCA-2011-3.2-0732, No. 23/2012.
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©2015 by De Gruyter
Artikel in diesem Heft
- Frontmatter
- Modulation of Electron-Acoustic Waves in a Plasma with Vortex Electron Distribution
- Linear Generalized Synchronization Using Bidirectional Coupling
- On the Exact Solutions of the Thomas Equation by Algebraic Methods
- On the Soliton Solution and Jacobi Doubly Periodic Solution of the Fractional Coupled Schrödinger–KdV Equation by a Novel Approach
- Modelling and Optimization of CO2 Absorption in Pneumatic Contactors Using Artificial Neural Networks Developed with Clonal Selection-Based Algorithm
- Analysis of Stochastic Nonlinear Dynamics in the Gear Transmission System with Backlash
- Chemical Reaction Effects in Maxwell Fluid Flow Over Permeable Surface: Dual Solutions
Artikel in diesem Heft
- Frontmatter
- Modulation of Electron-Acoustic Waves in a Plasma with Vortex Electron Distribution
- Linear Generalized Synchronization Using Bidirectional Coupling
- On the Exact Solutions of the Thomas Equation by Algebraic Methods
- On the Soliton Solution and Jacobi Doubly Periodic Solution of the Fractional Coupled Schrödinger–KdV Equation by a Novel Approach
- Modelling and Optimization of CO2 Absorption in Pneumatic Contactors Using Artificial Neural Networks Developed with Clonal Selection-Based Algorithm
- Analysis of Stochastic Nonlinear Dynamics in the Gear Transmission System with Backlash
- Chemical Reaction Effects in Maxwell Fluid Flow Over Permeable Surface: Dual Solutions