Cybernetic Approach to Modeling Greenhouse Dynamics

C.P. Glackin,; N.H. Siddique,

doi:10.1515/JISYS.2008.17.S1.27

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Cybernetic Approach to Modeling Greenhouse Dynamics

C.P. Glackin, und N.H. Siddique,

Veröffentlicht/Copyright: 1. Dezember 2008

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Aus der Zeitschrift Journal of Intelligent Systems Band 17 Heft Supplement

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Harvard
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Glackin,, C.P. and Siddique,, N.H.. "Cybernetic Approach to Modeling Greenhouse Dynamics" Journal of Intelligent Systems, vol. 17, no. Supplement, 2008, pp. 27-56. https://doi.org/10.1515/JISYS.2008.17.S1.27

Glackin,, C. & Siddique,, N. (2008). Cybernetic Approach to Modeling Greenhouse Dynamics. Journal of Intelligent Systems, 17(Supplement), 27-56. https://doi.org/10.1515/JISYS.2008.17.S1.27

Glackin,, C. and Siddique,, N. (2008) Cybernetic Approach to Modeling Greenhouse Dynamics. Journal of Intelligent Systems, Vol. 17 (Issue Supplement), pp. 27-56. https://doi.org/10.1515/JISYS.2008.17.S1.27

Glackin,, C.P. and Siddique,, N.H.. "Cybernetic Approach to Modeling Greenhouse Dynamics" Journal of Intelligent Systems 17, no. Supplement (2008): 27-56. https://doi.org/10.1515/JISYS.2008.17.S1.27

Glackin, C, Siddique, N. Cybernetic Approach to Modeling Greenhouse Dynamics. Journal of Intelligent Systems. 2008;17(Supplement): 27-56. https://doi.org/10.1515/JISYS.2008.17.S1.27

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Published Online: 2008-12

Artikel in diesem Heft

CONTENTS
Editorial: Cybernetic systems: Fuzzy, Neural and Evolutionary Computing Approaches
Nature Inspired Neural Network Ensemble Learning
Cybernetic Approach to Modeling Greenhouse Dynamics
Automatic Regularization of Multilayered-Perceptron Training by Weight Orthogonalization
Genetic Algorithm-based Modeling and Optimization of Control Parameters of an Air Motor
Genetic Programming Control of an Articulated Robotic Manipulator
Genetic Algorithm Optimization and Control System Design of Flexible Structures
Particle Swarm Intelligence to Optimize the Learning of N-tuples
State Estimation Methods for Sound Environment System Based on a Fuzzy Probability Theory

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Artikel in diesem Heft

CONTENTS
Editorial: Cybernetic systems: Fuzzy, Neural and Evolutionary Computing Approaches
Nature Inspired Neural Network Ensemble Learning
Cybernetic Approach to Modeling Greenhouse Dynamics
Automatic Regularization of Multilayered-Perceptron Training by Weight Orthogonalization
Genetic Algorithm-based Modeling and Optimization of Control Parameters of an Air Motor
Genetic Programming Control of an Articulated Robotic Manipulator
Genetic Algorithm Optimization and Control System Design of Flexible Structures
Particle Swarm Intelligence to Optimize the Learning of N-tuples
State Estimation Methods for Sound Environment System Based on a Fuzzy Probability Theory