<conference paper>
Neural networks and genetic algorithm approaches to auto-design of fuzzy systems
Creator | |
---|---|
Language | |
Publisher | |
Date | |
Source Title | |
First Page | |
Last Page | |
Conference | |
Publication Type | |
Access Rights | |
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 |
Hide fulltext details.
File | FileType | Size | Views | Description |
---|---|---|---|---|
IntConf016 | 3.17 MB | 294 |
Details
NCID | |
---|---|
Record ID | |
Related ISBN | |
Created Date | 2021.08.16 |
Modified Date | 2021.08.16 |