Weather Parameters Forecasting as Variables for Rainfall Prediction using Adaptive Neuro Fuzzy Inference System (ANFIS) and Support Vector Regression (SVR)

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D.C.R. Novitasari, H. Rohayani, Suwanto, Arnita, Rico, R. Junaidi, Rr D N Setyowati, R. Pramulya, F. Setiawan

2020 Journal of Physics: Conference Series Vol. 1501 Issue 1 Conference paper Cited by 19

Abstract

The weather anomaly phenomenon that occurs can have some negative impact such as flooding, floods will paralyze the economic activities of the community, transportation activities, damage public infrastructure. In this research forecasting weather parameters as a variable for predicting the amount of rainfall using the ANFIS method and Support Vector Regression (SVR) with the aim to provide information on future weather conditions quickly and accurately. The people can prepare themselves and prepare the equipment needed to deal with it. Rainfall predicted based on synop data such us relative humidity, wind, and temperature. Each parameters must forcasted by using ANFIS and the result used for predict rainfall. Accurate prediction calculated using MSE and RMSE. Predictions of parameters that affect rainfall using the ANFIS method shown that for wind speed predictions having RMSE of 1.975004, temperature predictions have RMSE of 0.742332, and predictions of relative humidity have RMSE of 3.871590. Predicted rainfall based on the data results of the nearest method pre-processing using the Support Vector Regression (SVR) method produces an MSE error value of 0.0928. © Published under licence by IOP Publishing Ltd.

Affiliations

Department of Mathematics, Uin Sunan Ampel Surabaya, Surabaya, Indonesia; Department of Information Technology, Adiwangsa Jambi University, Jambi, Indonesia; Department of Mathematics, Universitas Negeri Medan, Medan, Indonesia; Department of Architecture, Uin Sunan Ampel Surabaya, Surabaya, Indonesia; Department of Environmental Engineering, Uin Sunan Ampel Surabaya, Surabaya, Indonesia; Faculty of Agriculture, University Teuku Umar, Aceh, Indonesia; Forecaster and Analyst, Meteorological Climatological and Geophysics Agency, Surabaya, Indonesia