Journal of Ecology and Rural Environment ›› 2010, Vol. 26 ›› Issue (6): 600-604.doi:

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Evaluation of Eco-Environment Level Based on Decision-Tree-Based Support Vector Machine With Parameters Optimized by Genetic Algorithm

CHEN Hai-yang;TENG Yan-guo;WANG Jin-sheng   

  • Received:2010-06-28 Online:2010-11-25 Published:2011-04-11

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 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.

Key words: decision-tree-based support vector machine(DTBSVM), genetic algorithm, evaluation of eco-environment level, management of eco-environment