•  
  •  
 

International Journal of Advanced Technology in Civil Engineering

Abstract

Cascade feed forward ANN models have been developed by using pH, Alkalinity, Hardness, TS and MPN as the input variables to forecast water quality index (WQI) in the various zones of municipal distribution system. Different ANN models were developed using training data set and tested in order to determine optimum number of neurons in the hidden layer and best fitting transfer function. The study reveals that the predictions by logsigmoidal and pure linear transfer function are in good correlation with observed WQI as compared to tansigmoidal transfer function. It is also observed that the model performance changes considerably with change in hidden layer neurons. Hidden layer structure with seven neurons performs better, followed by hidden layer structure with four neurons and one neuron respectively.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.