基于RS-SVM模型的风暴潮灾害损失测度

论文以现有的风暴潮灾害研究为基础,通过构建评估指标体系提出了基于粗糙集-支持向量机模型(RS-SVM模型)的风暴潮灾害损失测度方法。RS-SVM模型较好的将二者优点进行结合,消除数据冗余信息的同时可以快速、准确解决非线性问题。在上述研究的基础上,对比单纯使用SVM方法与RS-SVM组合使用下的风暴潮经济损失测度效果,发现粗糙集与支持向量机在数据属性约简并进行预测过程中,确保了较高的拟合度与较低的误差率。

The assessment of storm surge disaster loss based on RS-SVM model

In this paper,we summarized the existing research about storm surge disaster,then Rough set-Support vector machine model is proposed for evaluating storm surge disaster losses through reasonable indicator system.The RS-SVM model could eliminate redundant data information,meanwhile,the model will achieve solving nonlinear problems quickly and accurately.In the later study,comparing the results about assessing storm surge losses under SVM model and RS-SVM model,we found that RS-SVM model ensured higher goodness of fit and lower error rate in the process of classification and prediction.