Artificial Intelligence in Textile Engineering explains Artificial Intelligence techniques from first principles in the perfect way for textiles materials scientists and engineers.
Advances in Artificial Intelligence technology have made a substantial impact across the textiles supply chain, making products more efficient, flexible and reliable. In this book techniques such as artificial neural network, support vector machine, fuzzy logic, rough set, evolutionary algorithm, and hybrid intelligence systems are described with application to textiles. Readers are supported throughout with step by step mathematical derivations of AI techniques, case studies, as well as MATLAB codes, giving readers from different backgrounds the perfect entry to AI solutions.
1. Chapter 1 Introduction - p. 1 2. Chapter 2 Artificial neural network - p. 7 3. Chapter 3 Support vector machines - p. 47 4. Keywords - p. 47 5. 3.1 Introduction - p. 47 6. 3.2 Support vector classification (SVC) - p. 47 7. 3.3 Support vector regression (SVR) - p. 79 8. 3.4 MATLAB coding - p. 92 9. 3.5 Summary - p. 103 10. References - p. 103 11. Chapter 4 Fuzzy logic - p. 105 12. Chapter 5 Rough set - p. 143 13. Chapter 6 Nature-inspired optimization algorithms - p. 171 14. Keywords - p. 171 15. 6.1 Introduction - p. 171 16. 6.2 Genetic algorithm (GA) - p. 171 17. 6.3 Particle swarm optimization (PSO) - p. 200 18. 6.4 Ant colony optimization (ACO) - p. 207 19. 6.5 MATLAB coding - p. 224 20. 6.6 Summary - p. 230 21. References - p. 231 22. Chapter 7 Hybrid artificial intelligence systems - p. 233 23. Keywords - p. 233 24. 7.1 Introduction - p. 233 25. 7.2 ANFIS - p. 233 26. 7.3 GFES - p. 256 27. 7.4 MATLAB coding - p. 276 28. 7.5 Summary - p. 293 29. References - p. 293 30. Index - p. 295
Artificial Intelligence in Textile Engineering explains Artificial Intelligence techniques from first principles in the perfect way for textiles materials scientists and engineers.
Advances in Artificial Intelligence technology have made a substantial impact across the textiles supply chain, making products more efficient, flexible and reliable. In this book techniques such as artificial neural network, support vector machine, fuzzy logic, rough set, evolutionary algorithm, and hybrid intelligence systems are described with application to textiles. Readers are supported throughout with step by step mathematical derivations of AI techniques, case studies, as well as MATLAB codes, giving readers from different backgrounds the perfect entry to AI solutions.
1. Chapter 1 Introduction - p. 1 2. Chapter 2 Artificial neural network - p. 7 3. Chapter 3 Support vector machines - p. 47 4. Keywords - p. 47 5. 3.1 Introduction - p. 47 6. 3.2 Support vector classification (SVC) - p. 47 7. 3.3 Support vector regression (SVR) - p. 79 8. 3.4 MATLAB coding - p. 92 9. 3.5 Summary - p. 103 10. References - p. 103 11. Chapter 4 Fuzzy logic - p. 105 12. Chapter 5 Rough set - p. 143 13. Chapter 6 Nature-inspired optimization algorithms - p. 171 14. Keywords - p. 171 15. 6.1 Introduction - p. 171 16. 6.2 Genetic algorithm (GA) - p. 171 17. 6.3 Particle swarm optimization (PSO) - p. 200 18. 6.4 Ant colony optimization (ACO) - p. 207 19. 6.5 MATLAB coding - p. 224 20. 6.6 Summary - p. 230 21. References - p. 231 22. Chapter 7 Hybrid artificial intelligence systems - p. 233 23. Keywords - p. 233 24. 7.1 Introduction - p. 233 25. 7.2 ANFIS - p. 233 26. 7.3 GFES - p. 256 27. 7.4 MATLAB coding - p. 276 28. 7.5 Summary - p. 293 29. References - p. 293 30. Index - p. 295
