Flood Prediction Model using Artificial Neural Network

Abstract

This paper presents a Flood Prediction Model (FPM) to predict flood in rivers using Artificial Neural Network (ANN) approach. This model predicts river water level from rainfall and present river water level data. Though numbers of factors are responsible for changes in water level, only two of them are considered. Flood prediction problem is a non-linear problem and to solve this nonlinear problem, ANN approach is used. Multi Linear Perceptron (MLP) based ANN’s Feed Forward (FF) and Back Propagation (BP) algorithm is used to predict flood. Statistical analysis shows that data fit well in the model. We present our simulation results for the predicted water level compared to the actual water level. Results show that our model successfully predicts the flood water level 24 hours ahead of time.