Iterative genetic-fuzzy learning for plant automation

A methodology of learning fuzzy rules using a genetic algorithm (GA). Through observations on a series of control actions from an expert, we aim to let the system derive a control model to emulate the expert's decision-making process in monitoring a plant.

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Bibliographic Details
Main Author:	Ng, Wil Lie.
Other Authors:	Lim, Meng Hiot
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:	http://hdl.handle.net/10356/4971
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Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-4971
record_format	dspace
spelling	sg-ntu-dr.10356-49712023-07-04T15:06:17Z Iterative genetic-fuzzy learning for plant automation Ng, Wil Lie. Lim, Meng Hiot School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence A methodology of learning fuzzy rules using a genetic algorithm (GA). Through observations on a series of control actions from an expert, we aim to let the system derive a control model to emulate the expert's decision-making process in monitoring a plant. Master of Engineering 2008-09-17T10:02:28Z 2008-09-17T10:02:28Z 2004 2004 Thesis http://hdl.handle.net/10356/4971 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Ng, Wil Lie. Iterative genetic-fuzzy learning for plant automation
description	A methodology of learning fuzzy rules using a genetic algorithm (GA). Through observations on a series of control actions from an expert, we aim to let the system derive a control model to emulate the expert's decision-making process in monitoring a plant.
author2	Lim, Meng Hiot
author_facet	Lim, Meng Hiot Ng, Wil Lie.
format	Theses and Dissertations
author	Ng, Wil Lie.
author_sort	Ng, Wil Lie.
title	Iterative genetic-fuzzy learning for plant automation
title_short	Iterative genetic-fuzzy learning for plant automation
title_full	Iterative genetic-fuzzy learning for plant automation
title_fullStr	Iterative genetic-fuzzy learning for plant automation
title_full_unstemmed	Iterative genetic-fuzzy learning for plant automation
title_sort	iterative genetic-fuzzy learning for plant automation
publishDate	2008
url	http://hdl.handle.net/10356/4971
_version_	1772827040448249856

Iterative genetic-fuzzy learning for plant automation

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