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Journal of Applied Sciences
  Year: 2007 | Volume: 7 | Issue: 15 | Page No.: 2006-2010
DOI: 10.3923/jas.2007.2006.2010
 
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Prediction of Clarified Water Turbidity of Moyog Water Treatment Plant Using Artificial Neural Network
Duduku Krishnaiah, Siva Kumar Kumaresan , Matthew Isidore and Rosalam Sarbatly

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.
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How to cite this article:

Duduku Krishnaiah, Siva Kumar Kumaresan , 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: 2006-2010.

DOI: 10.3923/jas.2007.2006.2010

URL: https://scialert.net/abstract/?doi=jas.2007.2006.2010

 
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