Prediction of Data from Pollution Sources Based on Elman Neural Network

Journal of South China University of Technology (Natural Science Edition) ›› 2009, Vol. 37 ›› Issue (5): 135-138.

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Prediction of Data from Pollution Sources Based on Elman Neural Network

Zhang Qi¹ Xu Zhi-jian¹ Zhao Kun-rong²

1. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, Guangdong, China; 2. South China Institute of Environment Science, Ministry of Environmental Protection, Guangzhou 510655, Guangdong, China

Received:2008-05-21 Revised:2008-07-18 Online:2009-05-25 Published:2009-05-25
Contact: 张齐（1963-），男，副教授，主要从事智能控制、信息处理、监控软件研究． E-mail:csqzhang@scut．edu．cn
About author:张齐（1963-），男，副教授，主要从事智能控制、信息处理、监控软件研究．
Supported by:
广东省科技计划项目（200713030100001）;广州市科技攻关计划项目（200523190191）

Abstract

Abstract:

In order to provide valuable prediction data for the decision making of environmental protection, a model to predict the data of pollution sources is proposed based on Elman neural network. By using the proposed model and by taking SO2--the main pollutant in the atmosphere--as an object, the complex relationships between SO2 concentration and the factors, including the air temperature, the relative humidity, the wind speed, the time and the historical date, are investigated. After training, the proposed model is used to perform a simulation. The results demonstrate that the outputs calculated with the proposed model accord well with the sample outputs, and that the proposed model is more effective than the prediction model based on BP neural network.

Key words: pollution source, prediction, Elman, neural network

Zhang Qi Xu Zhi-jian Zhao Kun-rong . Prediction of Data from Pollution Sources Based on Elman Neural Network[J]. Journal of South China University of Technology (Natural Science Edition), 2009, 37(5): 135-138.

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Prediction of Data from Pollution Sources Based on Elman Neural Network

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