| 基于GA参数寻优的决策树支持向量机生态环境质量评价方法 |
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| 引用本文： | 陈海洋,滕彦国,王金生.基于GA参数寻优的决策树支持向量机生态环境质量评价方法[J].生态与农村环境学报,2010,26(6). |
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| 作者姓名： | 陈海洋 滕彦国 王金生 |
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| 作者单位： | 北京师范大学水科学研究院,北京,100875 |
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| 基金项目： | 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) |
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| 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。
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| 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 |
Evaluation of Eco-Environment Level Based on Decision-Tree-Based Support Vector Machine With Parameters Optimized by Genetic Algorithm |
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| CHEN Hai-yang,TENG Yan-guo,WANG Jin-sheng.Evaluation of Eco-Environment Level Based on Decision-Tree-Based Support Vector Machine With Parameters Optimized by Genetic Algorithm[J].Journal of Ecology and Rural Environment,2010,26(6). |
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| Authors: | CHEN Hai-yang TENG Yan-guo WANG Jin-sheng |
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| Institution: | CHEN Hai-yang,TENG Yan-guo,WANG Jin-sheng(College of Water Science,Beijing Normal University,Beijing 100875,China) |
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| Abstract: | 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 mod... |
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| Keywords: | decision-tree-based support vector machine(DTBSVM) genetic algorithm evaluation of eco-environment level management of eco-environment |
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