Statistic Approach Versus Artificial Intelligence For Rainfall Prediction Based On Data Series

Statistic Approach Versus Artificial Intelligence For Rainfall Prediction Based On Data Series

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

Abstract

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