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Computational Intelligence [electronic resource] :Methods and Techniques / by Leszek Rutkowski.

by Rutkowski, Leszek [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Description: online resource.ISBN: 9783540762881.Subject(s): Engineering | Artificial intelligence | Mathematics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics) | Applications of Mathematics | Control, Robotics, Mechatronics | Operations Research/Decision TheoryDDC classification: 519 Online resources: Click here to access online
Contents:
Selected issues of artificial intelligence -- Methods of knowledge representation using rough sets -- Methods of knowledge representation using type-1 fuzzy sets -- Methods of knowledge representation using type-2 fuzzy sets -- Neural networks and their learning algorithms -- Evolutionary algorithms -- Data clustering methods -- Neuro-fuzzy systems of Mamdani, logical and Takagi-Sugeno type -- Flexible neuro-fuzzy systems.
In: Springer eBooksSummary: This book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. Those techniques are today commonly applied issues of artificial intelligence, e.g. to process speech and natural language, build expert systems and robots. The first part of the book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next various neural network architectures are presented and their learning algorithms are derived. Moreover, the family of evolutionary algorithms is discussed, in particular the classical genetic algorithm, evolutionary strategies and genetic programming, including connections between these techniques and neural networks and fuzzy systems. In the last part of the book, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared. This well-organized modern approach to methods and techniques of intelligent calculations includes examples and exercises in each chapter and a preface by Jacek Zurada, president of IEEE Computational Intelligence Society (2004-05).
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Selected issues of artificial intelligence -- Methods of knowledge representation using rough sets -- Methods of knowledge representation using type-1 fuzzy sets -- Methods of knowledge representation using type-2 fuzzy sets -- Neural networks and their learning algorithms -- Evolutionary algorithms -- Data clustering methods -- Neuro-fuzzy systems of Mamdani, logical and Takagi-Sugeno type -- Flexible neuro-fuzzy systems.

This book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. Those techniques are today commonly applied issues of artificial intelligence, e.g. to process speech and natural language, build expert systems and robots. The first part of the book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next various neural network architectures are presented and their learning algorithms are derived. Moreover, the family of evolutionary algorithms is discussed, in particular the classical genetic algorithm, evolutionary strategies and genetic programming, including connections between these techniques and neural networks and fuzzy systems. In the last part of the book, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared. This well-organized modern approach to methods and techniques of intelligent calculations includes examples and exercises in each chapter and a preface by Jacek Zurada, president of IEEE Computational Intelligence Society (2004-05).

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