JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2011, Vol. 41 ›› Issue (2): 163-166.

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Study on the reliability of heating regulation based on prediction using
the  BP neural network and regression

LIU Qingtang1, GUO Jingqiang2, SHAN Baoyan3, LI Ming1, PAN Jihong4   

  1. 1. Housing and UrbanRural Construction Bureau of Shandong Province, Jinan 250001, China;
    2. Yishui Municipal Company, Yishui 276400, China; 3. Shandong Jianzhu University, Jinan 250001, China;
    4. School of Energy and Power Engineering, Shandong University, Jinan 250061, China
  • Received:2010-03-23 Online:2011-04-16 Published:2010-03-23

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Abstract:

To meet the operational regulation demand of heating system, a study was conducted on the prediction of supply water temperature and water flux in a heating system. 200 groups of operating parameters were selected as samples from a certain period of a practical heating system, processed with matlab7.0, and predicted and analyzed with the back propagation neural network and regression. The former determined a reasonable back propagation network structure,and was  processed and trained with traingdm function. The latter fit a regression equation with high confidence level. Finally,  predicted values of supply temperature and water flux were  compared with the actual values while their errors were analyzed. The result showed that the two forecast values were reliable, but the back propagation neural network had a better result and smaller error.

Key words: heating regulation, neural network, regression, prediction

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