[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.13160/ricns.2020.13.1.34

An Impact Analysis and Prediction of Disaster on Forest Fire

Kim, Youn Su (Department of Computer Science and Statistics, Chosun University)
Lee, Yeong Ju (Department of Computer Science and Statistics, Chosun University)
Chang, In Hong (Department of Computer Science and Statistics, Chosun University)

Publication Information

Journal of Integrative Natural Science / v.13, no.1, 2020 , pp. 34-40 More about this Journal

Abstract

This study aims to create a model for predicting the number of extinguishment manpower to put out forest fires by taking into account the climate, the situation, and the extent of the damage at the time of the forest fires. Past research has been approached to determine the cause of the forest fire or to predict the occurrence of a forest fire. How to deal with forest fires is also a very important part of how to deal with them, so predicting the number of extinguishment manpower is important. Therefore predicting the number of extinguishment manpower that have been put into the forest fire is something that can be presented as a new perspective. This study presents a model for predicting the number of extinguishment manpower inputs considering the scale of the damage with forest fire on a scale bigger than 0.1 ha as data based on the forest fire annual report(Korea Forest Service; KFS) from 2015 to 2018 using the moderated multiple regression analysis. As a result, weather factors and extinguished time considering the damage show that affect forest fire extinguishment manpower.

Keywords

Correlation Analysis; Damaged Amount; Damaged Area; Extinguishment Manpower; Forest Fire; Moderated Multiple Regression Analysis;

Citations & Related Records

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