Genetic fuzzy systems : a paradigm for learning heuristic rules
298 p.
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2009
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Online Access: | http://hdl.handle.net/10356/19656 |
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sg-ntu-dr.10356-196562023-07-04T15:30:55Z Genetic fuzzy systems : a paradigm for learning heuristic rules Rahardja Sunarto Lim, Meng Hiot School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems 298 p. 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. Master of Engineering 2009-12-14T06:20:08Z 2009-12-14T06:20:08Z 1996 1996 Thesis http://hdl.handle.net/10356/19656 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Rahardja Sunarto Genetic fuzzy systems : a paradigm for learning heuristic rules |
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298 p. |
author2 |
Lim, Meng Hiot |
author_facet |
Lim, Meng Hiot Rahardja Sunarto |
format |
Theses and Dissertations |
author |
Rahardja Sunarto |
author_sort |
Rahardja Sunarto |
title |
Genetic fuzzy systems : a paradigm for learning heuristic rules |
title_short |
Genetic fuzzy systems : a paradigm for learning heuristic rules |
title_full |
Genetic fuzzy systems : a paradigm for learning heuristic rules |
title_fullStr |
Genetic fuzzy systems : a paradigm for learning heuristic rules |
title_full_unstemmed |
Genetic fuzzy systems : a paradigm for learning heuristic rules |
title_sort |
genetic fuzzy systems : a paradigm for learning heuristic rules |
publishDate |
2009 |
url |
http://hdl.handle.net/10356/19656 |
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1772827331681845248 |