Prediction of total concentration for spherical and tear shape drops by using neural network

In this study, the development of an alternative approach based on the Artificial Intelligent technique called Artificial Neural Network (ANN) was carried out. This report presents a new application of ANN techniques to the modeling of prediction total concentration of drops in the Rotating Disc Con...

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Main Author:	Saharun, Norhusna
Format:	Thesis
Language:	English
Published:	2013
Subjects:	HD30.2 Knowledge management
Online Access:	http://eprints.utm.my/id/eprint/47942/25/NorhusnaSaharunMFS2013.pdf
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id	my-utm-ep.47942
record_format	uketd_dc
spelling	my-utm-ep.479422017-07-17T08:09:53Z Prediction of total concentration for spherical and tear shape drops by using neural network 2013-06 Saharun, Norhusna HD30.2 Knowledge management In this study, the development of an alternative approach based on the Artificial Intelligent technique called Artificial Neural Network (ANN) was carried out. This report presents a new application of ANN techniques to the modeling of prediction total concentration of drops in the Rotating Disc Contactor Column (RDC). The ANN was trained with the simulated data based on spherical and tear-shaped drops, which consider ten classes volume of drops. The comparison result between Neural Network output and Mathematical Model output is presented. With 4 hidden nodes, the Neural Network models are able to generate the smallest MSE for each ten classes volume of drops. Then the neural network model is then being applied to the combination for all shape drops, which are spherical and tear shape drops as the inputs. The Neural Network models are able to predict 400 simulated data for combination spherical and tear shape drops with MSE error value 68482.6?E. The results with the smallest MSE presented in this paper shows that the Neural Network Model works successfully in prediction total concentration of multiple shape drops in ten classes volumes. 2013-06 Thesis http://eprints.utm.my/id/eprint/47942/ http://eprints.utm.my/id/eprint/47942/25/NorhusnaSaharunMFS2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	HD30.2 Knowledge management
spellingShingle	HD30.2 Knowledge management Saharun, Norhusna Prediction of total concentration for spherical and tear shape drops by using neural network
description	In this study, the development of an alternative approach based on the Artificial Intelligent technique called Artificial Neural Network (ANN) was carried out. This report presents a new application of ANN techniques to the modeling of prediction total concentration of drops in the Rotating Disc Contactor Column (RDC). The ANN was trained with the simulated data based on spherical and tear-shaped drops, which consider ten classes volume of drops. The comparison result between Neural Network output and Mathematical Model output is presented. With 4 hidden nodes, the Neural Network models are able to generate the smallest MSE for each ten classes volume of drops. Then the neural network model is then being applied to the combination for all shape drops, which are spherical and tear shape drops as the inputs. The Neural Network models are able to predict 400 simulated data for combination spherical and tear shape drops with MSE error value 68482.6?E. The results with the smallest MSE presented in this paper shows that the Neural Network Model works successfully in prediction total concentration of multiple shape drops in ten classes volumes.
format	Thesis
qualification_level	Master's degree
author	Saharun, Norhusna
author_facet	Saharun, Norhusna
author_sort	Saharun, Norhusna
title	Prediction of total concentration for spherical and tear shape drops by using neural network
title_short	Prediction of total concentration for spherical and tear shape drops by using neural network
title_full	Prediction of total concentration for spherical and tear shape drops by using neural network
title_fullStr	Prediction of total concentration for spherical and tear shape drops by using neural network
title_full_unstemmed	Prediction of total concentration for spherical and tear shape drops by using neural network
title_sort	prediction of total concentration for spherical and tear shape drops by using neural network
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2013
url	http://eprints.utm.my/id/eprint/47942/25/NorhusnaSaharunMFS2013.pdf
_version_	1747817269162934272

Prediction of total concentration for spherical and tear shape drops by using neural network

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