A neural fuzzy system for soft computing

Ö Ciftcioglu*, M. S. Bittermann, I. S. Sariyildiz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Citations (Scopus)

Abstract

An innovative neural fuzzy system is considered for soft computing in design. A neural tree structure is considered with nodes of neuronal type, where Gaussian function plays the role of membership function. The total tree structure effectively works as a fuzzy logic system having system inputs and outputs. In the system, as result of special provisions, the locations of the Gaussian membership functions of non-terminal nodes happen to be unity, so that the system has several desirable features; it represents a fuzzy model maintaining the transparency and effectiveness while dealing with complexity. The research is described in detail and its outstanding merits are pointed out in a framework having transparent fuzzy modeling properties and addressing complexity issues at the same time. A demonstrative application of the model is presented from a demonstrative simple architectural design exercise and the favorable performance for similar applications is highlighted.

Original languageEnglish
Title of host publicationNAFIPS 2007
Subtitle of host publication2007 Annual Meeting of the North American Fuzzy Information Processing Society
Pages489-495
Number of pages7
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventNAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society - San Diego, CA, United States
Duration: 24 Jun 200727 Jun 2007

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

ConferenceNAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society
Country/TerritoryUnited States
CitySan Diego, CA
Period24/06/0727/06/07

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