A Back Propagation Neural Network Model based on kalman filter for water quality prediction

Abstract

The Back Propagation Neural Network Model has some disadvantages to decrease prediction accuracy. Combining the advantages of the Kalman filter, a new Back Propagation Neural Network Model Based on Kalman Filter is established for the prediction of the water pollutants concentration. The result of the case study shows that the method proposed can effectively improve the prediction accuracy, and the improved model is proved to be a better and more effective method in water quality prediction.