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DNA Computing Based Genetic Algorithm

Applications in Industrial Process Modeling and Control

Specificaties
Gebonden, blz. | Engels
Springer Nature Singapore | e druk, 2020
ISBN13: 9789811554025
Rubricering
Springer Nature Singapore e druk, 2020 9789811554025
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities. 

Specificaties

ISBN13:9789811554025
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Singapore

Inhoudsopgave

Introduction.- DNA computing based RNA-GA.- DNA double-helix based hybrid genetic algorithm.- DNA computing based multi-objective genetic algorithm.- Parameter identification and optimization for chemical process.- RBF neural network for nonlinear SISO system.- T-S Fuzzy neural network for nonlinear SISO system.- PCA & GA based ARX plus RBF Modeling for Nonlinear DPS.- GA based predictive control design.- MOGA based PID controller design.- Concluding Remarks.

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        DNA Computing Based Genetic Algorithm