Abraham Kandel, Gideon Langholz

Hybrid Architectures for Intelligent Systems (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 448
• Erscheinungstermin: 10. September 2020
• Englisch
• ISBN-13: 9781000102949
• Artikelnr.: 60128129

Autorenporträt

Abraham Kandel and Gideon Langholz

Inhaltsangabe

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