DNA Computing Based Genetic Algorithm - Applications in Industrial Process Modeling and Control (Hardcover, 1st ed. 2020)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Release date:	July 2020
First published:	2020
Authors:	Jili Tao • Ridong Zhang • Yong Zhu
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	274
Edition:	1st ed. 2020
ISBN-13:	978-981-15-5402-5
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	981-15-5402-1
Barcode:	9789811554025

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