Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.

Combining multiple neural networks appears to be a very promising approach in improving neural network generalisation since it is very difficult, if not impossible, to develop a perfect single neural network (SNN) especially when dealing with a real time data.

Bibliographic Details
Main Authors: Ahmad, Zainal, Roslin, Fairuoze
Format: Conference or Workshop Item
Language:English
Published: 2007
Subjects:
Online Access:http://eprints.usm.my/15576/
http://eprints.usm.my/15576/1/real.pdf
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author Ahmad, Zainal
Roslin, Fairuoze
author_facet Ahmad, Zainal
Roslin, Fairuoze
author_sort Ahmad, Zainal
building USM Institutional Repository
collection Online Access
description Combining multiple neural networks appears to be a very promising approach in improving neural network generalisation since it is very difficult, if not impossible, to develop a perfect single neural network (SNN) especially when dealing with a real time data.
first_indexed 2025-11-15T15:53:48Z
format Conference or Workshop Item
id usm-15576
institution Universiti Sains Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T15:53:48Z
publishDate 2007
recordtype eprints
repository_type Digital Repository
spelling usm-155762017-11-20T07:22:06Z http://eprints.usm.my/15576/ Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique. Ahmad, Zainal Roslin, Fairuoze TK1-9971 Electrical engineering. Electronics. Nuclear engineering Combining multiple neural networks appears to be a very promising approach in improving neural network generalisation since it is very difficult, if not impossible, to develop a perfect single neural network (SNN) especially when dealing with a real time data. 2007 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.usm.my/15576/1/real.pdf Ahmad, Zainal and Roslin, Fairuoze (2007) Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique. In: International Conference on Control, Instrumentation and Mechatronics Engineering (CIM’07), 28 – 29 May 2007, Johor Bahru, Johor, Malaysia,.
spellingShingle TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Ahmad, Zainal
Roslin, Fairuoze
Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.
title Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.
title_full Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.
title_fullStr Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.
title_full_unstemmed Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.
title_short Modeling of real pH Neutralization Process using Multiple Neural Networks (MNN) Combination Technique.
title_sort modeling of real ph neutralization process using multiple neural networks (mnn) combination technique.
topic TK1-9971 Electrical engineering. Electronics. Nuclear engineering
url http://eprints.usm.my/15576/
http://eprints.usm.my/15576/1/real.pdf