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Estimating the Texas Windstorm Insurance Association claim payout of commercial buildings from Hurricane Ike

机译:估算得克萨斯州暴风雨保险协会向飓风艾克索赔的商业建筑物的支出

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Following growing public awareness of the danger from hurricanes and tremendous demands for analysis of loss, many researchers have conducted studies to develop hurricane damage analysis methods. Although researchers have identified the significant indicators, there is currently a shortage of comprehensive research for identifying the relationship among the vulnerabilities, natural disasters, and insured losses associated with individual buildings. To address this lack of research, this study will identify vulnerabilities and hazard indicators, develop metrics to measure the influence of economic losses from hurricanes, and visualize the spatial distribution of vulnerability to evaluate overall hurricane damage. This paper has utilized the Geographic Information System to facilitate collecting and managing data, and has combined vulnerability factors to assess the financial losses suffered by Texas coastal counties. A multiple regression method has been applied to develop hurricane damage prediction models. To reflect the pecuniary loss, insured loss payment was used as the dependent variable to predict the actual financial damage. Exposures, built environment vulnerability indicators, and hazard indicators were all used as independent variables. Accordingly, the models and findings may possibly provide vital references for government agencies and emergency planners to establish the hurricane damage mitigation strategies. In addition, insurance companies could utilize the model to predict hurricane damage.
机译:随着公众日益意识到飓风带来的危险以及对损失分析的巨大需求,许多研究人员进行了研究以开发飓风损害分析方法。尽管研究人员已经确定了重要的指标,但是目前缺乏用于确定脆弱性,自然灾害和与个别建筑物相关的保险损失之间关系的综合研究。为了解决这一缺乏研究的问题,本研究将识别脆弱性和危害指标,制定度量标准以衡量飓风对经济损失的影响,并可视化脆弱性的空间分布,以评估整体飓风的破坏程度。本文利用了地理信息系统来促进数据的收集和管理,并结合了脆弱性因素来评估德克萨斯州沿海县遭受的经济损失。多元回归方法已用于开发飓风破坏预测模型。为了反映金钱损失,将保险损失付款作为因变量来预测实际财务损失。暴露,建筑环境脆弱性指标和危害指标均用作自变量。因此,这些模型和发现可能为政府机构和应急计划制定者建立飓风损害缓解策略提供重要参考。另外,保险公司可以利用该模型来预测飓风的破坏。

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