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

机译:基于计量经济学模型组的中国风暴潮灾害损失评估

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摘要

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.
机译:风暴潮已经成为限制中国沿海地区经济和社会发展的重要因素。为了提高对未来风暴潮破坏的科学判断,提出了一种模型组方法,以完善风暴潮造成的损失评估。由于自然属性数据(登录中心气压,最大风速,最大暴雨水,超预警水位等)的相对分散性和不规则性,暴雨浪潮灾难根据八种暴风浪灾难等级划分划分方法,结合风暴潮水,超警惕潮位和灾害损失。风暴潮灾害损失评估模型组由八个方程组成,并构建了六个主要模块:农业损失,渔业损失,人力资源损失,工程设施损失,生活设施损失和直接经济损失的风暴潮灾害。最后,使用支持向量机(SVM)模型评估损失和样本内预测。结果表明,模型组的方程可以详细反映风暴潮破坏与其他相关变量之间的关系。基于原始值和预测值误差的比较,模型组通过了测试,为防灾减灾的早期布局提供了科学的支持和决策依据。

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