摘要
提出并实现了一种基于地形条件和领域知识的保险洪灾损失预测模型,根据数字高程模型生成地形及排水能力因子,利用神经网络模型的非线性映射能力进行仿真建模,并给出了在该模型中融合领域知识的方法.实验证明,该模型可得出动态的预测结果并具有较强的泛化能力,为保险及相关行业提供了一个可操作的洪灾损失预测处理平台.
A Flood Loss Prediction Model for insurance based on terrain condition and domain knowledge is proposed and implemented. By this model the terrain and drainage ability factor is generated based on Digital Elevation Model（DEM）, and Neural Network is used with its powerful non-linear mapping ability. A method to incorporate domain knowledge with this model is given. Experiments demonstrate that the model can generate dynamic predictions and has good generalization ability. It could provide an operable flood loss prediction platform for insurance and related industries.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2005年第11期2523-2529,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家"十五"科技攻关计划(2001BA102A05-02)
关键词
洪灾损失预测模型
地形条件
领域知识
数字高程模型
神经网络
flood loss prediction model
terrain condition
domain knowledge
digital elevation model
neural network
