Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and ApplicationsКНИГИ » ПРОГРАММИНГ
Название: Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications Автор: Oscar Castillo, Patricia Melin Издательство: Springer Год: 2021 Страниц: 382 Язык: английский Формат: pdf (true), epub Размер: 59.8 MB
We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their application in 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. 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 presents theory and practice of meta-heuristics in different areas of application.
Another group of papers describe diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical applications. 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 problems.
The convolutional neural networks or also commonly called CNN, are used for image classification and recognition mainly, the first layers can detect lines, curves and specialize until they reach deeper layers that recognize complex shapes such as a face or the silhouette of an animal or anything object. The convolutional neural network are used in In conjunction with many methods, one of these is fuzzy systems, which in many cases help the network to be more effective in recognizing images as in Choi is a CNN output optimization method to improve the precision of low precision classes, or in Kh-Madhloom et al. where CNN is combined with fuzzy logic to more accurately recognize the smile on the human face or the use a fuzzy control system was used in a robot, which previously implemented a classification navigation approach.
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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications 
Название: Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications
