| 基于RBF神经网络的水体污染物含量建模与预测 |
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| 引用本文： | 秦军,王定成.基于RBF神经网络的水体污染物含量建模与预测[J].江南大学学报(自然科学版),2010,9(1):52-55. |
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| 作者姓名： | 秦军 王定成 |
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| 作者单位： | 南京信息工程大学,计算机与软件学院,南京,210044 |
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| 摘 要： | 对水体中污染物含量进行预测具有十分重要的意义。将时间序列作为RBF神经网络的输入，对水体污染物含量的预测做了建模研究。实验结果表明，RBF神经网络的输出值与实际值之间的误差在可以接受的范围，因此在实际应用中，可以将RBF网络方法作为一种考虑采用的方法。
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| 关 键 词： | RBF神经网络 时间序列 水体污染物 预测 |
Levels of Pollutants in Water Modeling and Forecasting Based on RBF Neural Network |
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| QIN Jun,WANG Ding-cheng.Levels of Pollutants in Water Modeling and Forecasting Based on RBF Neural Network[J].Journal of Southern Yangtze University:Natural Science Edition,2010,9(1):52-55. |
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| Authors: | QIN Jun WANG Ding-cheng |
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| Institution: | College of Computer and Software;Nanjing University of Information Science and Technology;Nanjing 210044;China |
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| Abstract: | Forecasting the levels of pollutants in water is greatly significant.The time series is taken as the input of RBF neural network,and a lot of research has been done on the forecasting the levels of pollutants in water.The experimental result indicates that the error between the output of the RBF neural network and the actual numerical values is in the acceptable range.As a result,the RBF network can be considered as an adoptable method in practice. |
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| Keywords: | RBF neural network time series pollutants in water forecast |
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