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Flood loss prediction of coastal city based on GM-ANN

机译:基于GM-ANN的沿海城市洪水损失预测

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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.
机译:洪水损失的预测在中国非常重要。在本文中,将考虑沿海城市的洪水因素,例如地质沉降率,海平面高度的上升,降水,城市排水管长度,全年的GDP和全年的人口,以预测洪水的损失。首先,将使用层次分析法确定洪水系数的权重。考虑到不同因素的特征,应用GM来获得洪水因素的预测值。然后将预测值和权重应用于人工神经网络方法,以获取沿海城市的洪水损失。最后,以深圳为例,验证了该方法与GM,DGM和ANN方法进行比较的可行性。

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