| 地面水质评价的RBF神经网络方法 |
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| 引用本文： | 李兴旺,董曼玲.地面水质评价的RBF神经网络方法[J].水土保持通报,2002,22(3):51-54. |
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| 作者姓名： | 李兴旺 董曼玲 |
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| 作者单位： | 1. 安徽水利水电职业技术学院,安徽,合肥,230601
2. 山东农业大学,山东,泰安,271018 |
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| 摘 要： | 借助神经网络方法处理非线性问题的优势 ,采用径向基函数 (RBF)来构造多层前馈 BP神经网络。根据某流域水系的水质监测的数据 ,建立一个对地面水质进行判别的多层前馈网络数学模型。以地面水质污染主要的 7项指标为训练样本 ,利用该网络对水质进行评价 ,并将计算结果与其它方法进行比较分析。结果表明 ,该方法收敛速度较快 ,预测精度很高 ,效果优于其它方法
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| 关 键 词： | 人工神经网络 BP网络 RBF网络 水质评价 |
| 文章编号： | 1000-288X(2002)03-0051-04 |
| 收稿时间： | 2002/2/28 0:00:00 |
| 修稿时间： | 2002年2月28日 |
RBFNetwork Method of Evaluating Water Quality |
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| LI Xing wang and DONG Man ling.RBFNetwork Method of Evaluating Water Quality[J].Bulletin of Soil and Water Conservation,2002,22(3):51-54. |
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| Authors: | LI Xing wang and DONG Man ling |
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| Institution: | Anhui Water and Electricity Profession Technology Institute, Hefei City 230601, China;Shandong Agriculture University, Taian City 271000, Shandong Province, China |
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| Abstract: | With the advantage of neural network in nonlinear problem, a radial basis function is used to improve conventional BP network. According to the condition of inspecting water quality in Dawen river of Huang river, the ANN model of evaluating water quality is put forward. The training stylebook takes 7 polluted target of this water quality as samples, and the water quality is evaluated using the trained network. The calculating results are analyzed and compared. This method is used to speed up the convergence and impove the performance. |
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| Keywords: | artificial neural network BP network RBF network water quality evaluation |
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