Hybrid Architectures for Intelligent Systems

Inbunden, Engelska, 1992

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Beskrivning

Hybrid architecture for intelligent systems is a new field of artificial intelligence concerned with the development of the next generation of intelligent systems. This volume is the first book to delineate current research interests in hybrid architectures for intelligent systems.The book is divided into two parts. The first part is devoted to the theory, methodologies, and algorithms of intelligent hybrid systems. The second part examines current applications of intelligent hybrid systems in areas such as data analysis, pattern classification and recognition, intelligent robot control, medical diagnosis, architecture, wastewater treatment, and flexible manufacturing systems.Hybrid Architectures for Intelligent Systems is an important reference for computer scientists and electrical engineers involved with artificial intelligence, neural networks, parallel processing, robotics, and systems architecture.

Produktinformation

Utgivningsdatum:1992-02-21
Mått:178 x 254 x 28 mm
Vikt:1 020 g
Format:Inbunden
Språk:Engelska
Antal sidor:448
Förlag:Taylor & Francis Inc
ISBN:9780849342295

Utforska kategorier

Informationsteknik: allmänt inom Data och IT

Mer om författaren

Abraham Kandel and Gideon Langholz

Innehållsförteckning

THEORY, METHODOLOGIES, ALGORITHMS. NEURAL NETS AND FUZZY LOGIC (A.F. da Rocha and R.R. Yager). Preliminary Concepts. Basic Components of Modular Neural Networks. Modular Networks. NODE ERROR ASSIGNMENT IN EXPERT NETWORKS (R.C. Lacher). Discrete Time Neural Computation. Node Error Assignment. Expert Network Backprop. Computational Experiments. LEARNING SYSTEM FOR GRAMMARS AND LEXICONS (J. D'souza and M. Schneider). Learning. Modifying the Lexicon. Modifying the Grammar. Creating a Grammar. Relationship between FEST and LSGL. INTEGRATION OF NEURAL NETWORK TECHNIQUES WITH APPROXIMATE REASONING IN KNOWLEDGE-BASED SYSTEMS (M.E. Cohen and D.L. Hudson). Approximate Reasoning in Knowledge-Based Systems. A Neural Network Learning Algorithm. Combined Techniques. A PARALLEL DISTRIBUTED APPROACH FOR KNOWLEDGE-BASED INFERENCE AND LEARNING (L-M Fu). A Knowledge-Based Neural Network. Inference. Learning. Evaluation. PERFORMANCE ISSUES OF A HYBRID SYMBOLIC, CONNECTIONIST ALGORITHM (L.O. Hall and S.G. Romaniuk). Network Structure. Learning. Analysis of Learning. Global Attribute Covering Algorithm. The Two Spirals Problem. Diagnosing Semiconductor Wafer Failures. A HYBRID ARCHITECTURE FOR FUZZY CONNECTIONIST EXPERT SYSTEM (R.J. Machado and A.F. da Rocha). Architecture of Fuzzy Connectionist Expert Systems. Example of an Application. MODELS AND GUIDELINES FOR INTEGRATING EXPERT SYSTEMS AND NEURAL NETWORKS (L.R. Medsker and D.L. Bailey). Models for ES/NN Synergy. Application Review. Guidelines for Developmental of Hybrid Systems. FUZZY HYBRID SYSTEMS (C. Posey, A. Kandel, and G. Langholz). Expert Systems. Neural Networks. Fuzzy Hybrid Systems. Conversion from Fuzzy Expert System to Neural Network. Knowledge Transfer from Neural Network to Expert System. Learning Results. HYBRID DISTRIBUTED/LOCAL CONNECTIONIST ARCHITECTURES (T. Samad). Distributed and Local Representations. Hybrid Distributed and Local Representations. Hybrid Distributed/Local Networks. A Connectionist Rule-Based Syste