Abstract
According to algorithm of support vector machine (SVM), flood risk assessment was summarized as a support vector problem. Based on SVM and geographic information system, the flood risk assessment model was established to evaluate the flood risk. Taking Beijiang River basin as an example, the research result shows that the highest risk zone is mainly located in Sihui, Qingyuan city, Fogang, northern Huaiji, Yang Shan, northern Yingde, Wengyuan, central Nanxiong and so on. Compared with a few historical floods, the result can better reflect the actual situation of flood risk in Beijiang River basin, which validates the rationality of the model and provides a reference for flood control and disaster assessment.
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