Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/19656| Title: | Genetic fuzzy systems : a paradigm for learning heuristic rules | Authors: | Rahardja Sunarto | Keywords: | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems | Issue Date: | 1996 | Abstract: | Fuzzy systems have been used extensively to solve many real-world control prob-lems. However, issues pertaining to the acquisition of the knowledge, particularly the control rules and membership functions of the fuzzy concepts persist. In our work, we propose a genetic fuzzy hybrid system that uses a genetic algorithm (GA) to directly ma-nipulate fuzzy control rules. This system uses a GA to derive an «-rule fuzzy system based on specified membership functions for the fuzzy control terms. | Description: | 298 p. | URI: | http://hdl.handle.net/10356/19656 | Schools: | School of Electrical and Electronic Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
| Appears in Collections: | EEE Theses |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| SunartoRahardja1996.pdf Restricted Access | Main report | 8.58 MB | Adobe PDF | View/Open |
Page view(s) 50
621
Updated on Mar 16, 2025
Download(s)
4
Updated on Mar 16, 2025
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.