Diagnosis based on fuzzy IF-THEN rules and genetic algorithms

Author

Rotshtein, Alexander P. ; Rakytyanska, Hanna B.

Author_Institution

Jerusalem Coll. of Technol. - Machon Lev, Jerusalem

fYear

2008

fDate

25-27 May 2008

Firstpage

328

Lastpage

333

Abstract

This paper proposes an approach for inverse problem solving based on the description of the interconnection between unobserved and observed parameters of an object (causes and effects) with the help of fuzzy IF-THEN rules. The essence of the approach proposed consists in formulating and solving the optimization problems, which, on the one hand, find the roots of fuzzy logical equations, corresponding to IF-THEN rules, and on the other hand, tune the fuzzy model on the readily available experimental data. The genetic algorithms are proposed for the optimization problems solving.

Keywords

diagnostic reasoning; fuzzy logic; fuzzy reasoning; fuzzy set theory; genetic algorithms; inverse problems; cause-effect interconnection; fuzzy IF-THEN rule-based diagnosis; fuzzy logical equation; fuzzy model tuning; fuzzy set theory; genetic algorithm; inverse problem solving; optimization problem solving; Biomedical engineering; Educational institutions; Equations; Fuzzy logic; Fuzzy set theory; Fuzzy systems; Genetic algorithms; Inverse problems; Medical diagnostic imaging; Problem-solving; diagnosis; fuzzy IF-THEN rules; fuzzy logical equations solving; fuzzy model tuning; inverse problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Human System Interactions, 2008 Conference on

Conference_Location

Krakow

Print_ISBN

978-1-4244-1542-7

Electronic_ISBN

978-1-4244-1543-4

Type

conf

DOI

10.1109/HSI.2008.4581458

Filename

4581458