Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].

Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].

Setiap proses kimia cenderung untuk mengalami kegagalan. Situasi ini memaksa industri dan penyelidik mencari teknik bersesuaian bagi mengesan kegagalan secepat yang mungkin. Every chemical processes prones to failure. This situation enforces the researchers and industrial to find the appropriate...

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Main Author: Syed Ab. Rahman, Syed Azhar
Format: Thesis
Language:English
Published: 2009
Subjects:
TP1-1185 Chemical technology
Online Access:http://eprints.usm.my/15590/1/MODELING_OF_FAULTS_FOR_CHEMICAL_BATCH_REACTOR_USING_ARTIFICIAL_NEURAL_NETWORK_AND_FUZZY_LOGIC.pdf
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spelling my-usm-ep.155902017-04-17T07:55:10Z Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185]. 2009-06 Syed Ab. Rahman, Syed Azhar TP1-1185 Chemical technology Setiap proses kimia cenderung untuk mengalami kegagalan. Situasi ini memaksa industri dan penyelidik mencari teknik bersesuaian bagi mengesan kegagalan secepat yang mungkin. Every chemical processes prones to failure. This situation enforces the researchers and industrial to find the appropriate techniques to detect a process failure as early as possible. 2009-06 Thesis http://eprints.usm.my/15590/ http://eprints.usm.my/15590/1/MODELING_OF_FAULTS_FOR_CHEMICAL_BATCH_REACTOR_USING_ARTIFICIAL_NEURAL_NETWORK_AND_FUZZY_LOGIC.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Kimia
institution Universiti Sains Malaysia
collection USM Institutional Repository
language English
topic TP1-1185 Chemical technology
spellingShingle TP1-1185 Chemical technology
Syed Ab. Rahman, Syed Azhar
Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].
description Setiap proses kimia cenderung untuk mengalami kegagalan. Situasi ini memaksa industri dan penyelidik mencari teknik bersesuaian bagi mengesan kegagalan secepat yang mungkin. Every chemical processes prones to failure. This situation enforces the researchers and industrial to find the appropriate techniques to detect a process failure as early as possible.
format Thesis
qualification_level Master's degree
author Syed Ab. Rahman, Syed Azhar
author_facet Syed Ab. Rahman, Syed Azhar
author_sort Syed Ab. Rahman, Syed Azhar
title Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].
title_short Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].
title_full Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].
title_fullStr Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].
title_full_unstemmed Modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [TP1-1185].
title_sort modelling of faults for chemical batch reactor using artificial neural network and fuzzy logic [tp1-1185].
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Kejuruteraan Kimia
publishDate 2009
url http://eprints.usm.my/15590/1/MODELING_OF_FAULTS_FOR_CHEMICAL_BATCH_REACTOR_USING_ARTIFICIAL_NEURAL_NETWORK_AND_FUZZY_LOGIC.pdf
_version_ 1747819872477249536

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