By Topic

A synthesis method of the approximate reasoning engine by means of genetic algorithm-neural net realization of any multiple-valued logic function using GA

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Yamamoto, Y. ; Takasaki City Univ. of Econ., Japan

In a series of papers, the author proposed an approximate reasoning method which expresses reasoning rules with one newly-defined infinitely-valued threshold function to use it as a reasoning engine, and discussed the advantages and limitations to the fuzzy reasoning. The subject of this paper is the remained problem: how to express the complicated reasoning rules containing non-linearity, non-unateness, etc. The problem is related to the multi-stage synthesis of multiple-valued threshold functions. A synthesis method using the genetic algorithm is devised here with some promising results of realization of arbitrary multiple-valued logic function by threshold functions

Published in:

Multiple-Valued Logic, 1998. Proceedings. 1998 28th IEEE International Symposium on

Date of Conference:

27-29 May 1998