Statistic Approach Versus Artificial Intelligence For Rainfall Prediction Based On Data Series
Vol.5 No.2 May 2013/International Journal of Engineering and Technology (IJET) (SCOPUS INDEX)
Indrabayu, A. Achmad, M.S. Pallu, N. Harun
This paper proposed a new idea in comparing two common predictors i.e. the statistic method and artificial intelligence (AI) for rainfall prediction using empirical data series. The statistic method uses Auto-Regressive Integrated Moving (ARIMA) and Adaptive Splines Threshold Autoregressive (ASTAR), most favorable statistic tools, while in the AI, combination of Genetic Algorithm-Neural Network (GA-NN) is chosen. The results show that ASTAR gives best prediction compare to others, in term of root mean square (RMSE) and following trend between prediction and actual. Keyword- Rain Prediction, ARIMA, ASTAR and GA-NN I.
Keyphrases: rainfall prediction statistic approach versus artificial intelligence data series doi statistic method common predictor new idea genetic algorithm-neural network favorable statistic tool root mean square empirical data series auto-regressive integrated moving prediction compare keyword rain prediction adaptive spline threshold autoregressive artificial intelligence