An Algorithm for Setting Sugeno-Type Fuzzy Inference Systems

An algorithm for tuning fuzzy inference systems of the Sugeno type of zero order based on statistical data is presented, which assumes the allocation of a set of reference points in the space of input variables, where the values of the output variable are calculated using linear regression. The resu...

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Bibliographic Details
Published inAutomatic documentation and mathematical linguistics Vol. 55; no. 3; pp. 79 - 88
Main Authors Golosovskiy, M. S., Bogomolov, A. V., Evtushenko, E. V.
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.05.2021
Springer Nature B.V
Subjects
Algorithms
Computer Science
Fuzzy systems
Information Storage and Retrieval
Information systems
Intelligent Systems
Statistical analysis
Statistical inference
System effectiveness
Sugeno-type system
fuzzy inference system
linear regression
fuzzy inference system tuning
intelligent information system
membership function
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ISSN0005-1055
1934-8371
DOI10.3103/S000510552103002X

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Summary:An algorithm for tuning fuzzy inference systems of the Sugeno type of zero order based on statistical data is presented, which assumes the allocation of a set of reference points in the space of input variables, where the values of the output variable are calculated using linear regression. The results of the algorithm are presented, showing the effectiveness of its application for the synthesis of intelligent information systems for various purposes.
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ISSN:0005-1055
1934-8371
DOI:10.3103/S000510552103002X