Neural networks and genetic algorithm approaches to auto-design of fuzzy systems - Collections

＜conference paper＞
Neural networks and genetic algorithm approaches to auto-design of fuzzy systems

Creator	Author PID 0000-0002-1431-9472 K002333 Creator Name Takagi, Hideyuki 高木, 英行タカギ, ヒデユキ Affiliation Affiliation Name Computer Science Division, University of California, Berkeley カリフォルニア大学
Creator	Creator Name LEE, Michael Affiliation Affiliation Name Computer Science Division, University of California, Berkeley カリフォルニア大学
Language	English
Publisher	Springer
Date	1993-06-28
Source Title	Fuzzy Logic in Artificial Intelligence - 8th Austrian Artificial Intelligence Conference, FLAI 1993, Proceedings
First Page	68
Last Page	79
Conference	Name Austrian Artificial Intelligence Conference (FLAI) Sequence 8 Date June 28–30, 1993 Place Linz Country Australia
Publication Type	Accepted Manuscript
Access Rights	open access
Related DOI	isVersionOf http://dx.doi.org/10.1007/3-540-56920-0_9
Related DOI
Abstract	This paper presents Neural Network and Genetic Algorithm approaches to fuzzy system design, which aims to shorten development time and increase system performance. An approach that uses neural network... to represent multi-dimensional nonlinear membership functions and an approach to tune membership function parameters are given. A genetic algorithm approach that integrates and automates three fuzzy system design stages is also proposed.show more
Table of Contents	1 Introduction 2 Neural Network Approaches 3 Genetic Algorithm Approaches 4 Conclusion

File	FileType	Size	Views	Description
IntConf016	pdf	3.17 MB	293