Hybrid Intelligent Systems based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics

In this book, recent theoretical developments on fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are considered in application areas such as intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction, and optimization of complex problems. Nowadays, the main topics of the book are highly relevant, as most current intelligent systems and hardware implementations in use utilize some form of intelligent feature to enhance their performance. In addition, theoretically speaking, new and advanced models, and algorithms of type-2 fuzzy logic are presented, which will be of great interest to researchers in these areas. Also, novel nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript that are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.

• Fuzzy Logic
• Neural Networks
• Optimization Algorithms
• Artificial Intelligence
• Computational Intelligence

• Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, CP, Mexico

  Oscar Castillo, Patricia Melin