Bandung Rainfall Forecast and Its Relationship with Nino 3.4 Using Nonlinear Autoregressive Exogenous Neural Network

被引:5
|
作者
Pontoh, Resa Septiani [1 ]
Toharudin, Toni [1 ]
Ruchjana, Budi Nurani [2 ]
Sijabat, Novika [1 ]
Puspita, Mentari Dara [1 ]
机构
[1] Univ Padjadjaran, Fac Math & Nat Sci, Dept Stat, Sumedang 45363, Indonesia
[2] Univ Padjadjaran, Fac Math & Nat Sci, Dept Math, Sumedang 45363, Indonesia
关键词
rainfall; Bandung; Nino; 3; 4; NARX NN;
D O I
10.3390/atmos13020302
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The city of Bandung, as the capital city of West Java, is one of several areas in Indonesia with high rainfall. This situation can cause disasters, such as floods and landslides, that can harm many parties. Rainfall in Indonesia, particularly on the island of Java itself, is closely related to the global phenomenon of Nino 3.4. In the period from January 2001-November 2021, the rainfall and Nino 3.4 showed some extreme values. In order to foresee the disasters, an accurate rainfall forecast should be performed. For this reason, we try to construct a model of rainfall forecast and its relation to the global phenomenon of Nino 3.4 using the nonlinear autoregressive exogenous neural network (NARX NN). The result shows that NARX NN (13-7-1) with a Mean Absolute Percentage Error (MAPE) value of 6.26% and R-2 of 85.37% is best suited for the prediction of this phenomenon. In addition, this study provides forecast results for the next six periods, which can be used as a reference for the relevant authorities to foresee the possibility of flooding in Bandung city. From the forecast results, it can be concluded that the highest rainfall forecasts in the city of Bandung are in February 2022, and will slowly decrease in March 2022. To prevent hydro-meteorological disasters, such as floods in Bandung city, the community can clear waterways, such as clogged drains, rivers, and dams, as well as prepare tools for evacuation.
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页数:17
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