Fuzzy non-linear regression method for intensification of the object´s vagueness representation

Author

Pokorný, Miroslav

Author_Institution

Dept. of Meas. & Control, Tech. Univ. Ostrava, Czech Republic

Volume

4

fYear

1995

fDate

20-24 Mar 1995

Firstpage

2051

Abstract

The paper deals with problems of structural and parameters identification of nonlinear production models, which are based on regression methods and use the theory of fuzzy sets for representation of indeterminacy. The aim is to present a new generalized fuzzy nonlinear analysis and to formulate appropriate methodology of modeling and identification method. The paper presents the corresponding computer program module for real-time new nonlinear regression analysis and to carry out a numerical experiment

Keywords

fuzzy set theory; identification; statistical analysis; fuzzy nonlinear regression; fuzzy sets; generalized fuzzy nonlinear analysis; indeterminacy representation; nonlinear production models; object vagueness representation intensification; parameters identification; real-time nonlinear regression analysis; structural identification; Ear; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Informatics; Least squares methods; Linear regression; Parameter estimation; Production; Regression analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int

Conference_Location

Yokohama

Print_ISBN

0-7803-2461-7

Type

conf

DOI

10.1109/FUZZY.1995.409960

Filename

409960