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基于支持向量机的水质监测数据处理及状况识别与评价方法
Assessment Method of Water Quality of Monitoring Data Based on Support Vector Machine
【摘要】 水质评价实际上是一个监测数据处理与状态估计、识别的过程,提出一种基于支持向量机的方法应用于水质评价,该方法依据决策二叉树多类分类的思想,构建了基于支持向量机的水环境质量状况识别与评价模型。以长江口的实际水质监测数据为例进行了实验分析,并与单因子方法及单个BP神经网络方法进行了比较分析。实验结果表明,运用该模型对长江口的实际水质监测数据进行的综合水质评价效果较好,且具有较高的实用价值。
【Abstract】 The assessment of water quality is a fusion of multi-source information,state evaluation and identification.This paper introduces a method to assess the lake water quality eutrophication based on support vector machine.Using the idea of decision binary tree,it constitutes a assessment model of water quality of monitoring data based on SVM.This paper uses an experiment on the monitoring data of Yangtse River port and gives a comparison and analysis with single factor assessment method and the single BP neural network.The experiment shows the good effect of such model and have potential application value.
【Key words】 Support Vector Machine; Decision Binary Tree; BP Neural Networks; Assessment of Water Quality;
- 【文献出处】 计算机应用研究 ,Application Research of Computers , 编辑部邮箱 ,2006年09期
- 【分类号】TP274
- 【被引频次】30
- 【下载频次】315