摘要
选取决策树作为支持向量机多类分类方法,选择径向基核函数建立了生态环境质量决策树支持向量机评价模型,基于遗传算法实现了惩罚因子、核函数参数的自适应优选,并运用建立的模型对我国主要省市生态环境质量进行了评价。研究结果表明,该方法可以较好地实现生态环境质量评价。
To apply support vector machine(SVM) for evaluation of eco-environment,it is essential to give priority to designing the classifier and picking kernel functions,their parameters and penalty factors.Described here are the ways of choosing decision-tree as SVM multi-class classification method and radical base kernel functions to build a decision-tree-based SVM evaluation model for eco-environment level.Self-adaptive optimization of penalty factors and kernel function parameters is realized.The evaluation model is tested for eco-environment evaluation of some major cities and provinces of China.The test demonstrates that SVM is a good method to evaluate eco-environmental quality.
出处
《生态与农村环境学报》
CAS
CSSCI
CSCD
北大核心
2010年第6期600-604,共5页
Journal of Ecology and Rural Environment
基金
国家水体污染控制与治理科技重大专项(2009ZX07419-003
2008ZX07207-007)
教育部新世纪优秀人才支持计划(NECT-09-0230)
关键词
决策树支持向量机
遗传算法
生态环境质量评价
生态环境质量管理
decision-tree-based support vector machine(DTBSVM)
genetic algorithm
evaluation of eco-environment level
management of eco-environment