| dc.description.abstract |
Attempt has been made to create a Water Quality Index (WQI) based on artificial neural network (ANN) and globally accepted parameters. Several methods to measure WQI are available in the research and ambiguity problems exist where all the sub-indices of WQI are acceptable but overall index is not acceptable. In this study, we have tried to develop the WQI based on the WHO (world Health Organization) parameters (Dissolved Oxygen, pH, Turbidity, E. Coli and Electric Conductivity). The results also reveal changes in ANN based result from various input neural network model and its parameters. Even within same model, changes occur with variation in parameter. Based on the statistical parameter of regression value, the parameter and network model would be selected. With the dataset created for this study have shown the Cascade network is best for predicting the WQI. |
en_US |