New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics

In this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are applied to areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are some papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also some papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different areas of application. In addition, there are papers that present theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, there are some papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.

Klappentext

Automated Medical Diagnosis & Classification of Skin Diseases Using Efficinetnet-B0 Convolutional Neural Network.- Modular Approach for Neural Networks in medical image classi-fication with enhanced fuzzy integration.- Clustering and prediction of time series for traffic accidents using a nested layered artificial neural network model.

Inhalt
Automated Medical Diagnosis & Classification of Skin Diseases Using Efficinetnet-B0 Convolutional Neural Network.- Modular Approach for Neural Networks in medical image classi-fication with enhanced fuzzy integration.- Clustering and prediction of time series for traffic accidents using a nested layered artificial neural network model.