计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 421-424.doi: 10.11896/jsjkx.191200132
李宝胜1, 秦传东1,2
LI Bao-sheng1, QIN Chuan-dong1,2
摘要： 随着新能源汽车的推广,电动汽车逐渐进入千家万户,而影响电动汽车价格的因素较多。文中对影响电动汽车价格的20个属性进行主成分分析研究,先用Pearson相关系数法和PCA算法对数据进行预处理,获得比较重要的样本属性,然后对研究后的新数据进行多分类有监督学习。在支持向量机模型的基础上,用粒子群算法对支持向量机(Support Vector Machine,SVM)模型的参数进行优化选择,实现了对电动汽车的多分类研究,实验表明所建立的模型对电动汽车的多分类效果明显。
中图分类号:
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