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基于支持向量机的地下水质量综合评价
引用本文:司训练, 张旭峰. 基于支持向量机的地下水质量综合评价[J]. 环境工程学报, 2014, 8(10): 4340-4344.
作者姓名:司训练  张旭峰
作者单位:1.西安石油大学油气资源经济与管理研究中心, 西安 710065
摘    要:提出基于支持向量机(SVM)机器学习算法的地下水质量评价模型。首先给出了训练样本生成和数据规范化处理的具体方法,然后采用支持向量机的多分类算法构建模型,并使用k折交叉核实方法对参数进行验证优化。最后通过实证分析,并与单因子指数法、模糊综合评价法和BP神经网络法的评价结果对比分析可知,该方法简便易行,评价结果客观且准确度较高,具有很强的实用性。

关 键 词:支持向量机   地下水环境质量   多分类算法   综合评价
收稿时间:2014-07-03

Comprehensive evaluation of groundwater quality based on support vector machine
Si Xunlian, Zhang Xufeng. Comprehensive evaluation of groundwater quality based on support vector machine[J]. Chinese Journal of Environmental Engineering, 2014, 8(10): 4340-4344.
Authors:Si Xunlian  Zhang Xufeng
Affiliation:1.The Research Center of Oil and Gas Resource Economic and Management, Xi'an Shiyou University, Xi'an 710065, China
Abstract:A groundwater quality evaluation model was proposed based on support vector machine (SVM) algorithm.The specific methods of generating training samples and data generalization process were introduced.The model was established based on multi-class classifier of the SVM.And then,we used K-fold cross verification method to validate the parameter optimization.We compared the evaluation results of empirical analysis with the results obtained by single-factor index method,fuzzy comprehensive evaluation method and BP neural network method.The results demonstrate that the proposed model is convenience,high accuracy and high practicability.
Keywords:support vector machine(SVM)  groundwater environmental quality  multi-classification algorithm  comprehensive evaluation
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