Water Quality Prediction of Nainital Lake, Uttarakhand, India Using Artificial Neural Network Models

Abstract

Artificial neural networks have progressed in a rapid way in the field of soft computing, and it is widely used in forecasting. The work presented in this chapter is about the development of artificial neural network (ANN)-based models to forecast the water quality (WQ) in Nainital Lake, Uttarakhand, India. A dataset comprising pH, turbidity, and total dissolved solid (TDS) of time period 2018-2019 has been used and analyzed using MATLAB software. For experimentation purposes, four data partition strategies, 10 learning algorithms of back propagation neural network (BPNN), and different combinations of learning rates and training tolerance were evaluated. The performance of the model was evaluated using statistical methods such as MSE, RMSE, MAD, MAPE. The results of the experiment show the capability of the optimal ANN models to predict the WQ of Nainital Lake.