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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Optimization of Rules in Neuro-Fuzzy Inference Systems

verfasst von : J. Amudha, D. Radha

Erschienen in: Computational Vision and Bio Inspired Computing

Verlag: Springer International Publishing

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Abstract

Optimization of rule based system with Neuro Fuzzy Inference system results better regarding accuracy and interpretability. Dynamic Evolving Neuro Fuzzy Systems (DENFIS) model is used to find out an optimized rule base using computational intelligence techniques for a target search application. The process of optimization starts at the beginning of the target search process by selecting an appropriate selection of rule based Fuzzy Inference System. Further, optimization has been addressed in the choice of the number of rules by reducing the number of attributes used in the input. The integrated approach of input selection and rule selection results in accurate target predictions. The ability of knowledge-representation, highly interpretable if…then rules and imprecision tolerance are the major features of the proposed model.

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Vorheriges Kapitel Enforcement of Automatic Penalty (e-Penalty) to Govern the Traffic Rule Violators in Digitized INDIA Using I.C.T.
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Metadaten
Titel
Optimization of Rules in Neuro-Fuzzy Inference Systems
verfasst von
J. Amudha
D. Radha
Copyright-Jahr
2018
Buch
Computational Vision and Bio Inspired Computing

Print ISBN: 978-3-319-71766-1

Electronic ISBN: 978-3-319-71767-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-71767-8_69

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