Sulfur Dioxide Emission Combination Prediction Model of China Thermal Power Industry

Zhou Jianguo, Zhang Fen

Abstract


The prediction of regional sulfur dioxide (SO2) emission of thermal power belongs to gray system which has small amounts of samples and little information, so a appropriate forecasting method is essential. Based on thermal power industry SO2 emission data from state department authorities, considering the main factors of China's thermal power industry SO2 predicted emission, we established a combination prediction model connecting gray prediction model with BP neural network model to predict SO2 emission, and we get more satisfied prediction.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2181


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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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