Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups

Xue Jin, Xiaoxia Shi, Jintian Gao, Tongbin Xu and Kedong Yin
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Xue Jin: School of Economics, Ocean University of China, Qingdao 266100, China
Xiaoxia Shi: School of Economics, Ocean University of China, Qingdao 266100, China
Jintian Gao: School of Economics, Ocean University of China, Qingdao 266100, China
Tongbin Xu: School of Economics, Ocean University of China, Qingdao 266100, China
Kedong Yin: School of Economics, Ocean University of China, Qingdao 266100, China

IJERPH, 2018, vol. 15, issue 4, 1-19

Abstract: Storm surge has become an important factor restricting the economic and social development of China’s coastal regions. In order to improve the scientific judgment of future storm surge damage, a method of model groups is proposed to refine the evaluation of the loss due to storm surges. Due to the relative dispersion and poor regularity of the natural property data (login center air pressure, maximum wind speed, maximum storm water, super warning water level, etc.), storm surge disaster is divided based on eight kinds of storm surge disaster grade division methods combined with storm surge water, hypervigilance tide level, and disaster loss. The storm surge disaster loss measurement model groups consist of eight equations, and six major modules are constructed: storm surge disaster in agricultural loss, fishery loss, human resource loss, engineering facility loss, living facility loss, and direct economic loss. Finally, the support vector machine (SVM) model is used to evaluate the loss and the intra-sample prediction. It is indicated that the equations of the model groups can reflect in detail the relationship between the damage of storm surges and other related variables. Based on a comparison of the original value and the predicted value error, the model groups pass the test, providing scientific support and a decision basis for the early layout of disaster prevention and mitigation.

Keywords: storm surge disaster; loss evaluation; grade classification; econometric model groups; support vector machines (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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