Automatic generation of membership function and fuzzy rule using inductive reasoning

Author

Kim, C.J. ; Russell, B. Don

Author_Institution

Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA

fYear

1993

fDate

1-3 Dec 1993

Firstpage

93

Lastpage

96

Abstract

This paper discusses the automatic generation of membership function and fuzzy rule. The generation of them are accomplished by utilizing the essential characteristic of the inductive reasoning which derives a general consensus from the particular. The induction is performed by the entropy minimization principle which clusters most optimally the parameters corresponding to the output classes. The rule derivation also provide the average probability of each step of rule, which is no other than the rule weight. The generation scheme is illustrated for practical use

Keywords

fuzzy logic; fuzzy set theory; inference mechanisms; knowledge based systems; probabilistic logic; automatic membership function generation; average probability; entropy minimization; fuzzy rules generation; induction machine; inductive reasoning; rule derivation; rule weight; Automatic control; Cement industry; Character generation; Entropy; Fuzzy logic; Fuzzy reasoning; Home appliances; Induction generators; Industrial control; Kilns;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Fuzzy Control and Intelligent Systems, 1993., IFIS '93., Third International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-1485-9

Type

conf

DOI

10.1109/IFIS.1993.324207

Filename

324207