DNA Computing Based Genetic Algorithm Applications in Industrial Process Modeling and Control
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,...
| Main Authors: | , , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2020, 2020
|
| Edition: | 1st ed. 2020 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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