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Numerical Simulation of Distributed Devices for the Processing of UltraWideband Information Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Fuzzy Rules Reduction in Knowledge Bases of Decision Support Systems by Objects State Evaluation

Authors : Maria Dagaeva, Aleksey Katasev

Published in: Cyber-Physical Systems: Modelling and Intelligent Control

Publisher: Springer International Publishing

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Abstract

The problem of eliminating the redundancy of knowledge bases formed based on fuzzy neural networks is considered. To solve this problem, fuzzy rules reduction technology based on the principles of knowledge taxonomy and genetic optimization was proposed. A technique for clustering fuzzy rules in the initial knowledge base has been developed with obtaining an intermediate knowledge base. To minimize the number of fuzzy rules in the intermediate knowledge base and obtain the required knowledge base, a genetic algorithm has been developed. A software package was developed on the basis of the proposed mathematical methods. The research carried out based on the software complex showed the effectiveness of the technology of fuzzy rules reduction and the possibility of its practical use.

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Metadata
Title
Fuzzy Rules Reduction in Knowledge Bases of Decision Support Systems by Objects State Evaluation
Authors
Maria Dagaeva
Aleksey Katasev
Copyright Year
2021
Book
Cyber-Physical Systems: Modelling and Intelligent Control

Print ISBN: 978-3-030-66076-5

Electronic ISBN: 978-3-030-66077-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-66077-2_9

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