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
Official URL: http://dx.doi.org/10.3923/jas.2007.2006.2010
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.
|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|
|Deposited By:||IR Admin|
|Deposited On:||29 Apr 2011 16:52|
|Last Modified:||18 Feb 2015 11:51|
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