The second edition of this book provides extensively updated coverage of fuzzy control and fuzzy systems. Particular emphasis is placed on the role of fuzzy sets in control engineering, to provide flexible control algorithms. Significant new material is included. The author first provides information on fuzzy sets and the concept of fuzzy control. He reviews selected applications, and highlights their origin. Later chapters consider design aspects and theoretical developments in the design of fuzzy controllers. A special emphasis is focused on the processing of fuzzy information with the aid of fuzzy relational structures and their extensions, giving rise to fuzzy neural networks. The book addresses a novel approach towards designing fuzzy controllers, which takes advantage of the knowledge representation capabilities of fuzzy sets and of the learning abilities of neural networks. There is also comprehensive coverage of the paradigms and algorithms of fuzzy modelling.

FUZZY CONTROL AND FUZZY SYSTEMS

Pedrycz

Science & Math

Research Studies Pre

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm’s algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

Deep Learning: Algorithms and Applications (Studies in Computational Intelligence, 865)

Computers & Technology

Computer Science

Springer

This volume is devoted to interactive and iterative processes of decision-making– I2 Fuzzy Decision Making, in brief. Decision-making is inherently interactive. Fuzzy sets help realize human-machine communication in an efficient way by facilitating a two-way interaction in a friendly and transparent manner. Human-centric interaction is of paramount relevance as a leading guiding design principle of decision support systems.
The volume provides the reader with an updated and in-depth material on the conceptually appealing and practically sound methodology and practice of I2 Fuzzy Decision Making. The book engages a wealth of methods of fuzzy sets and Granular Computing, brings new concepts, architectures and practice of fuzzy decision-making providing the reader with various application studies.
The book is aimed at a broad audience of researchers and practitioners in numerous disciplines in which decision-making processes play a pivotal role and serve as a vehicle to produce solutions to existing problems. Those involved in operations research, management, various branches of engineering, social sciences, logistics, and economics will benefit from the exposure to the subject matter. The book may serve as a useful and timely reference material for graduate students and senior undergraduate students in courses on decision-making, Computational Intelligence, operations research, pattern recognition, risk management, and knowledge-based systems.

Granular Computing and Decision-Making (Studies in Big Data, 10)

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Books by Pedrycz

See the best price to sell, buy, or rent books by Pedrycz. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

FUZZY CONTROL AND FUZZY SYSTEMS

Deep Learning: Algorithms and Applications (Studies in Computational Intelligence, 865)

Granular Computing and Decision-Making (Studies in Big Data, 10)