基于支持向量机的绿潮灾害影响因素的权重分析

根据2012~2013年南黄海海域绿潮浒苔遥感监测分布面积数据及温度、天气状况、风向、风力、浪高5个影响绿潮浒苔扩散的气候因子,建立了相应的支持向量机回归模型.通过模型中各影响因素权重的变化分析绿潮灾害的发展过程,并与传统的单因素分析法进行对比,支持向量机回归更能准确得出各影响因素的权重及权重的变化规律.通过对权重变化规律的分析,给出在绿潮发生过程中漂浮、爆发和消亡阶段的划分依据.

Weight analysis of each influence factor of the green tide disaster based on SVM

According to the green tide algae -Ulvaprolifera remote sensing data of the Southern Yellow Sea in 2012~2013, climate factors including temperature, weather, wind direction, wind force and wave height which effect theUlvaprolifera diffusion, the corresponding support vector regression model (SVR) was established. By analyzing the development of the disaster using the model’s weight change, the result of SVM was more accurately draw the right weight of each factor and weight conversion lawcompared with traditional single factor analysis method. Then through the analysis for the change rule of weight, give the division basis of the various stages of green tide.