Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups
| Autor: | Xue Jin, Kedong Yin, Tongbin Xu, Xiaoxia Shi, Jintian Gao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
China
Support Vector Machine 010504 meteorology & atmospheric sciences Meteorology Health Toxicology and Mutagenesis animal diseases Stormwater lcsh:Medicine Storm surge Natural property 010501 environmental sciences 01 natural sciences Wind speed Article support vector machines econometric model groups Disasters Humans Weather 0105 earth and related environmental sciences Emergency management business.industry storm surge disaster loss evaluation grade classification lcsh:R Public Health Environmental and Occupational Health Water level Econometric model Environmental science business Models Econometric |
| Zdroj: | International Journal of Environmental Research and Public Health International Journal of Environmental Research and Public Health; Volume 15; Issue 4; Pages: 604 International Journal of Environmental Research and Public Health, Vol 15, Iss 4, p 604 (2018) |
| ISSN: | 1660-4601 1661-7827 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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