违反了 PRIMARY KEY 约束 'PK_t_counter'。不能在对象 'dbo.t_counter' 中插入重复键。 语句已终止。 基于人工智能技术的热带气旋灾害评估方法研究:以广东省为例-A Study on Evaluation Method of Tropical Cyclone Disaster Assessment Based on Artificial Intelligence Technology:Taking Guangdong Province as an Example
doi:  10.3878/j.issn.1006-9585.2018.18001
基于人工智能技术的热带气旋灾害评估方法研究:以广东省为例

A Study on Evaluation Method of Tropical Cyclone Disaster Assessment Based on Artificial Intelligence Technology:Taking Guangdong Province as an Example
摘要点击 284  全文点击 389  投稿时间:2018-01-02  
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基金:  国家自然科学基金41475064、41605069、41475073
中文关键词:  热带气旋灾害评估  县域单元  经济灾损率  人口受灾率  演化建模
英文关键词:  Tropical cyclones disaster assessment  County unit  Economic loss rate  Affected people rate  Evolutionary modeling
           
作者中文名作者英文名单位
张文ZHANG Wen南京邮电大学通达学院, 江苏扬州 225127
赵珊珊ZHAO Shanshan国家气候中心, 北京 100081;南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044
万仕全WAN Shiquan扬州市气象局, 江苏扬州 225009
封国林FENG Guolin国家气候中心, 北京 100081
引用:张文,赵珊珊,万仕全,封国林.2018.基于人工智能技术的热带气旋灾害评估方法研究:以广东省为例[J].气候与环境研究,23(4):504-512,doi:10.3878/j.issn.1006-9585.2018.18001.
Citation:ZHANG Wen,ZHAO Shanshan,WAN Shiquan,FENG Guolin.2018.A Study on Evaluation Method of Tropical Cyclone Disaster Assessment Based on Artificial Intelligence Technology:Taking Guangdong Province as an Example[J].Climatic and Environmental Research(in Chinese),23(4):504-512,doi:10.3878/j.issn.1006-9585.2018.18001.
中文摘要:
      基于历史观测资料,系统地研究了广东省热带气旋(tropical cyclone,TC)风雨及其带来的直接经济损失的空间分布特征。结果表明,粤西沿海地区受TC大风影响最为频繁,但TC经济灾损率和受灾频次在粤西和粤东较重。根据广东省TC风雨和直接经济损失的空间分布特征,将广东分为粤西、粤东、珠三角和粤北4个区域,进而利用演化建模方法建立了广东省各区域TC经济灾损率评估模型。该评估模型模拟的TC经济灾损率与实际值的相关系数达0.66以上,基于该模型对独立样本的预测检验结果与实际值的相关系数达到0.61以上(显著性水平a=0.05)。这表明,基于演化建模方法建立的广东省各区域评估模型在广东省TC灾害评估中有着潜在的应用价值。
Abstract:
      The spatial distribution characteristics of tropical cyclone (TC) rainfall and direct economic losses incurred by TCs in Guangdong Province are systematically studied based on historical observation data. The results show that the coastal areas of western Guangdong are most frequently affected by TC winds, whereas the economic loss rates and disaster frequencies are much larger in the southwestern and eastern seashore areas of Guangdong. According to the spatial distribution characteristics of TC precipitation, high winds and rate of economic loss, Guangdong Province is divided into four regions. The evolutionary modeling method is then used to build the assessment model of TC economic loss rate in each region. The correlation coefficient between the simulated TC economic loss rate and the actual value is larger than 0.66, and the correlation coefficient between the pre-evaluation results and the actual values of independent samples reaches above 0.61 (significant at the level of a=0.05). This result shows that the regional assessment model based on the evolutionary modeling method has potential application value in the assessment of TC disaster in Guangdong Province.
主办单位:中国科学院大气物理研究所 单位地址:北京市9804信箱
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