震灾经济损失评估的遗传神经网络模型
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摘要
地震灾害造成的直接经济损失与很多因素有关:致灾因子强度,主要包括地震震级、发震时间及地点、震源深度和地震动输入参数等;受灾体密度,主要包括衡量城市经济和社会发展水平的人口密度、城市密度、建筑物密度和财产密度等;城市抵抗地震灾害的能力。这里选取震级、地震动输入参数、人均国内生产总值GDP、受灾面积和灾区人口密度作为网络的输入节点,用直接经济损失率作为网络的输出节点,建立了基于遗传神经网络的震灾经济损失评估模型,对地震灾害所造成的经济损失进行评估,实例验证了该方法的有效性。
Generally speaking,many factors affect economic losses of seismic disaster and they include:firstly,the disaster-causing factors such as the earthquake's magnitude, time, place and input parameters of ground motion; secondly, the density of disaster-affected body which is the indexes assessing the economy and development of cities such as population density, city density, building density and wealth density; lastly, the city's ability against earthquake disaster.This paper mainly selects the magnitude of earthquake, the input parameters of ground motion, per capita GDP, the disaster-suffered area and population density as input nodes while the rate of direct economic loss as output node.In this paper,the assessment model of seismic losses based on the genetic algorithm and artificial neural networks is made, which is used to assess the seismic losses.
Generally speaking,many factors affect economic losses of seismic disaster and they include:firstly,the disaster-causing factors such as the earthquake's magnitude, time, place and input parameters of ground motion; secondly, the density of disaster-affected body which is the indexes assessing the economy and development of cities such as population density, city density, building density and wealth density; lastly, the city's ability against earthquake disaster.This paper mainly selects the magnitude of earthquake, the input parameters of ground motion, per capita GDP, the disaster-suffered area and population density as input nodes while the rate of direct economic loss as output node.In this paper,the assessment model of seismic losses based on the genetic algorithm and artificial neural networks is made, which is used to assess the seismic losses.
引文
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[2]陈其福,等.地震损失预测评估中的易损性分析[J].中国地震,1999,15(2):97-103.
[3]陈其福,等.全球地震灾害预测[J].科学通报,1999,44(1):21-23.
[4]杨行峻,郑君里.人工神经网络与盲信号处理[M].北京:清华大学出版社,2003.
[5]苑希民,等,神经网络和遗传算法在水利领域的应用[M].北京:中国水利水电出版社,2002.
[6]聂高众,等.中国未来10-15年地震灾害的风险评估[J].自然灾害学报,2002,11(1):69-72.
[7]李娟,等.中亚地区地震损失评估[J].内陆地震,2000,14(1):1-8.
[8]陈棋福,等.利用国内生产总值和人口数据进行地震灾害损失预测评估[J].地震学报,1997,19(6):641-649.
[9]张晓东,朱丽霞.地震灾害经济损失理论估计及初步讨论[J].西北地震学报,1998,20(2):59-61.
[10]郭恩栋,等.生命线工程震害损失快速评估系统[J].世界地震工程,2000,16(3):17-18.
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