Cargando…
Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups
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 r...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5923646/ https://www.ncbi.nlm.nih.gov/pubmed/29584628 http://dx.doi.org/10.3390/ijerph15040604 |
_version_ | 1783318391297146880 |
---|---|
author | Jin, Xue Shi, Xiaoxia Gao, Jintian Xu, Tongbin Yin, Kedong |
author_facet | Jin, Xue Shi, Xiaoxia Gao, Jintian Xu, Tongbin Yin, Kedong |
author_sort | Jin, Xue |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5923646 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-59236462018-05-03 Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups Jin, Xue Shi, Xiaoxia Gao, Jintian Xu, Tongbin Yin, Kedong Int J Environ Res Public Health Article 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. MDPI 2018-03-27 2018-04 /pmc/articles/PMC5923646/ /pubmed/29584628 http://dx.doi.org/10.3390/ijerph15040604 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jin, Xue Shi, Xiaoxia Gao, Jintian Xu, Tongbin Yin, Kedong Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups |
title | Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups |
title_full | Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups |
title_fullStr | Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups |
title_full_unstemmed | Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups |
title_short | Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups |
title_sort | evaluation of loss due to storm surge disasters in china based on econometric model groups |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5923646/ https://www.ncbi.nlm.nih.gov/pubmed/29584628 http://dx.doi.org/10.3390/ijerph15040604 |
work_keys_str_mv | AT jinxue evaluationoflossduetostormsurgedisastersinchinabasedoneconometricmodelgroups AT shixiaoxia evaluationoflossduetostormsurgedisastersinchinabasedoneconometricmodelgroups AT gaojintian evaluationoflossduetostormsurgedisastersinchinabasedoneconometricmodelgroups AT xutongbin evaluationoflossduetostormsurgedisastersinchinabasedoneconometricmodelgroups AT yinkedong evaluationoflossduetostormsurgedisastersinchinabasedoneconometricmodelgroups |