Overview
- Provides step-by-step tutorials and program codes
- Presents GA applications for single-objective and multi-objective optimization in connection with nonlinear system modeling and distributed parameter system modeling
- Proposes control optimization methods from traditional PID controllers and advanced model predictive controls to advanced fuzzy controllers
- Introduces the newest topics in deep learning and CNN
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Authors and Affiliations
About the authors
Jili Tao received her B.Sc. and Ph.D. from Central South University and Zhejiang University, China, in 2004 and 2007, respectively. She is currently a Professor at the Institute of Ningbo Technology, Ningbo, China. Her research interests include intelligent optimization, modeling and its applications to electronic system design and control system design.
Ridong Zhang received his Ph.D. in Control Science and Engineering from Zhejiang University, Hangzhou, China, in 2007. From 2007 to 2015, he was a Full Professor with the Institute of Information and Control, Hangzhou Dianzi University, Hangzhou. Since 2015, he has been a Visiting Professor at the Chemical and Biomolecular Engineering Department, Hong Kong University of Science and Technology. His research interests include process modeling, model predictive control and nonlinear systems.
Yong Zhu, received M.Sc. degrees from HangZhou DianZi University, China, in 2004. He is currently a lecturer in the Institute of Ningbo technology, Ningbo, China. Meanwhile he has been a Ph.D. candidate in Ningbo University. His present research interests in electronic system design and advanced control system design.
Bibliographic Information
Book Title: DNA Computing Based Genetic Algorithm
Book Subtitle: Applications in Industrial Process Modeling and Control
Authors: Jili Tao, Ridong Zhang, Yong Zhu
DOI: https://doi.org/10.1007/978-981-15-5403-2
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-5402-5Published: 01 July 2020
Softcover ISBN: 978-981-15-5405-6Published: 01 July 2021
eBook ISBN: 978-981-15-5403-2Published: 01 July 2020
Edition Number: 1
Number of Pages: IX, 274
Number of Illustrations: 79 b/w illustrations, 108 illustrations in colour
Topics: Computational Science and Engineering, Control and Systems Theory, Artificial Intelligence