支持向量机与模糊综合指数法在水质评价中的应用  

作　　者：李昂 水西霞 员佳慧 李嫣 

机构地区：[1]华北水利水电大学,河南郑州450046 [2]三门峡市陕州区计划节约用水管理中心,河南三门峡472000 [3]中建七局总承包公司河南分公司,河南郑州450012

出　　处：《科技创新与应用》2022年第10期181-184,共4页Technology Innovation and Application

摘　　要：水质评价是解决水体污染和保护水环境的基础,文章利用分类支持向量机、回归支持向量机和模糊综合指数法对实例进行水质综合评价。两种支持向量机均采用萤火虫算法优化相关的学习参数。最终得到的评价结果显示,进行参数优化后的分类支持向量机和回归支持向量机评价结果更优,在反映整体水质的同时,能区别个别因子情况;模糊综合指数法直观明了,可以作为一种辅助性水质评价方法。Water quality evaluation is the basis of solving water pollution and protecting water environment.In this paper,classification support vector machine,regression support vector machine and fuzzy comprehensive index method are used to comprehensively evaluate water quality.The two kinds of support vector machines use firefly algorithm to optimize the relevant learning parameters.The final evaluation results show that the evaluation results of classification support vector machine and regression support vector machine after parameter optimization are better,which can not only reflect the overall water quality,but also distinguish individual factors,and the fuzzy comprehensive index method is intuitive and clear.it can be used as an auxiliary method for water quality evaluation.

关 键 词：水质评价 模糊综合指数法 分类支持向量机 回归支持向量机 

分 类 号：X824[环境科学与工程—环境工程]