A Back Propagation Neural Network Model Based on Kalman Filter for Water Quality Prediction

被引：0

作者：

Zhao, Yanfei ^{[1
]}

Zou, Zhihong ^{[1
]}

Wang, Shenglong ^{[1
]}

机构：

[1] Beihang Univ, Sch Econ & Management, Beijing, Peoples R China

来源：

2015 11TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC) | 2015年

关键词：

water quality prediction; Kalman filter; Back Propagation Neural Network;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The Back Propagation Neural Network Model has some disadvantages to decrease prediction accuracy. Combining the advantages of the Kalman filter, a new Back Propagation Neural Network Model Based on Kalman Filter is established for the prediction of the water pollutants concentration. The result of the case study shows that the method proposed can effectively improve the prediction accuracy, and the improved model is proved to be a better and more effective method in water quality prediction.

引用

页码：149 / 153

页数：5

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