文章基本信息

标题：PREDICTING RAINFALL FROM WEATHER OBSERVATIONS USING SVM APPROACH FOR IDENTIFY THE PARAMETER OF FUEL MOISTURE CODE AS FIRE WEATHER INDEX
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作者：DARWIS ROBINSON MANALU ; MUHAMMAD ZARLIS ; HERMAN MAWENGKANG 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：16
语种：English
出版社：Journal of Theoretical and Applied
摘要：The Fine Fuel Moisture Code (FFMC) is a numeric rating of the dampness substance of litter and other restored fine fills. This code is a pointer of the general simplicity of start and the combustibility of fine fue. In this study we observed the rainfall time series as a parameter to get the index of FFMC. The main goal of this study to predict the amount of rainfall in a particular division or state well in advance. We predict the amount of rainfall using past data to generate the parameter of FFMC using SVM model in North Sumatera. Based on the result, the various visualizations of data are observed in Aek Godang, North Sumatera which helps in implementing the approaches for rainfall prediction to evaluate the parameter of fuel moisture code as fire weather index. The analysed individual year rainfall patterns for 2017, 2018, 2019, the approximately close means, noticed less standard deviations.
关键词：Rainfall;Predicting;FFMC;SVM Model;North Sumate