Prediction of clarified water turbidity of Moyog water treatment plant using artificial neural network

Krishnaiah, Duduku and Sivakumar Kumaresan, and Matthew Isidore, and Rosalam Sarbatly, (2007) Prediction of clarified water turbidity of Moyog water treatment plant using artificial neural network. Journal of Applied Sciences, 7 (15). pp. 2006-2010. ISSN 1812-5654

[img]
Preview
Text
Prediction_of_clarified_water_turbidity_of_Moyog_water_treatment_plant_using_artificial_neural_network.pdf

Download (203kB) | Preview

Abstract

This study outlines the artificial neural networks application to improve the prediction capability by investigating the effect of data sampling, network type and configuration as well as the inclusion of past data at the neural network input. Multi layered perception and Elman network were used. Validation results using input data based on 5 min and 1 h sampling was compared. It was found that the 1 h sampling yielded better prediction. Different network configurations were also compared and it was observed that although the larger network showed better prediction capability during the training phase, it was the smaller network that demonstrated better prediction in the validation stage. The inclusion of past data into the neural network was also studied. The generalisation degraded as more past data were included. © 2007 Asian Network for Scientific Information.

Item Type: Article
Uncontrolled Keywords: Artificial neural network, Coagulation control, Network validation, Water quality prediction
Subjects: ?? GB1201-1598 ??
?? TD429.5-480.7 ??
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 29 Apr 2011 08:52
Last Modified: 16 Oct 2017 05:13
URI: http://eprints.ums.edu.my/id/eprint/2901

Actions (login required)

View Item View Item

Browse Repository
Collection
   Articles
   Book
   Speeches
   Thesis
   UMS News
Search
Quick Search

   Latest Repository

Link to other Malaysia University Institutional Repository

Malaysia University Institutional Repository