Author(s): Sobri Harun; Van Thanh Nguyen

Linked Author(s): Sobri Harun

Keywords: RIMA; Forecast; Fuzzy; Inflow; Neural network

Abstract: Studies on the time series modeling of monthly reservoir inflows sequences using neural network method are presented. Based on multilayer perceptron (MLP) and radial basis function (RBF) methods, two types of neural network models were proposed to forecast the net inflow series into Pedu-Muda reservoir system in Kedah, Malaysia. The analyses determine the feasiblity and accuracy of neural network model in univariate forecasting of net inflows. Results of neural network forecast were compared with seasonal autoregresive integrated moving average (ARIMA) and adaptive fuzzy model (FM). The illustrative model's application indicates that MLP, RBF and FM models provide a promising forecast of net inflow series into a reservoir.

DOI:

Year: 2001