Название: Fuzzy Intelligent Systems: Methodologies, Techniques, and ApplicationsАвтор: E. Chandrasekaran, R. Anandan, G. Suseendran
Издательство: Wiley-Scrivener
Год: 2021
Страниц: 496
Язык: английский
Формат: pdf (true), epub
Размер: 64.1 MB
Fuzzy Intelligent Systems: Methodologies, Techniques and Applications comprises state-of-the-art chapters detailing how expert systems are built and the fuzzy logic resembling human reasoning powering them. Hybrid and neuro-fuzzy intelligent systems are discussed along with Evolutionary and, in particular, Genetic Algorithms. This approach has been extended by using Multiobjective Evolutionary Algorithms, which can consider multiple conflicting objectives instead of a single one. The book also discusses the hybridization between Multiobjective Evolutionary Algorithms and Fuzzy Systems which is known as Multiobjective Evolutionary Fuzzy Systems.
It is with immense pleasure that we introduce this book. Our objective in writing it is to foster advancements in the field and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and those in education and research covering a broad cross section of technical disciplines.
The format of the book was designed to match the self-contained approach to fuzzy mathematics and fuzzy control systems theory that even students with no prior knowledge can easily understand. It enables both classroom and self-directed learners to create a strong foundation in fuzzy systems by being open and straightforward; following a brief introduction to the subject, the authors dive right into real-world applications of fuzzy logic revealing its practical flavor. The book is mainly intended to familiarize systems and control subjects for both senior undergraduate and first-year graduate students, with the fundamental mathematical theory and design methodology needed to understand and use fuzzy control systems. This self-contained textbook will provide a solid framework for designing and evaluating fuzzy control systems under unpredictable and irregular conditions. Students can gain a thorough understanding of fuzzy control systems theory by mastering its contents.
Engineers, both current and future, need systematic training in the analytic theory and rigorous design of fuzzy control systems to keep up with and advance the rapidly evolving field of applied control technologies. As a consequence, expert systems with fuzzy-logic capabilities make for a more versatile and innovative handling of problems. This book attempts to showcase the combination of fuzzy logic and neural networks known as a neuro-fuzzy system, which should result in a hybrid intelligent system by combining a human-like reasoning style of neural networks.
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