基于GM-ANN的沿海城市洪水损失预测

Pengzhan Cui, Ye-qing Guan, Ying Zhu
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引用次数: 4

摘要

洪水损失预测在中国具有十分重要的意义。本文将考虑沿海城市的洪水因素,如地质沉降速率、海平面高度上升、降水、城市排水管道长度、全年GDP和人口等来预测洪水损失。首先,采用层次分析法确定洪水因子权重。考虑到不同因子的特点,采用遗传算法得到洪水因子的预测值。然后将预测值和权重应用于人工神经网络方法,得到沿海城市洪水损失。最后以深圳为例,对GM、DGM和ANN方法进行了比较,验证了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flood loss prediction of coastal city based on GM-ANN
Flood loss prediction is very important in China. In this paper, flood factors of coastal city, such as geological sedimentation rate, rise in sea level height, precipitation, urban drainage pipe length, annual GDP and population throughout the year will be considered to predict flood loss. Firstly, AHP will be used to determine the weight of flood factors. Considering the characteristics of different factors, GM is applied to get predictive values of flood factors. Then predictive values and weights are applied to ANN method to obtain flood loss of coastal city. Finally, Shenzhen is regarded as an example to verify the feasibility of this methods GM, DGM and ANN methods compared.
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