APPLICATION OF BACK PROPAGATION NEURAL NETWORK MODEL TO SIMULATE THE MONTHLY RUNOFFS AT TRI AN AND PHUOC HOA HYDROLOGICAL STATIONS TO FILL UP THE MISSING OF THE HISTORICAL DATA SERIES

Abstract

An artificial neural network is a mathematical model that was produced on the basis of the biological and psychological insights. In general, it can be applied to any problem to establish the functional relationship between input and output variables in a fuzzy manner. Due to the advance in theory, capability in computation and the convenience in practice, the artificial neural networks have been increasingly and widely applied in various engineering fields. In this paper, the back propagation neural network model is utilized to generate the monthly runoffs at Tri An and Phuoc Hoa hydrological stations. It is aimed at filling up the missing of historical hydrological data to serve for the planning, management and operation of reservoirs and other water resources system components in the Lower Dong Nai River Basin. The high fitness between simulated monthly runoff and measured data are obtained at these two hydrological stations using back propagation neural network model.