|Table of Contents|

College building energy consumption prediction based on GM-RBF neural network


Research Field:
Publishing date:


College building energy consumption prediction based on GM-RBF neural network
Zhao ChaoLin SimingXu Qiaoling
Chemistry and Chemical Engineering,Fuzhou University,Fuzhou 350108,China
college buildings energy consumption prediction grey theory radical basis function neural network combined models
To improve the accuracy of the forecasting of the college building energy consumption,this pape puts forward an estimating method of the building energy consumption according to the grey theory and radical basis function neural network(RBFNN).The proposed model combines the advantages of low data demand of grey theory with the self-learning and self-organization of RBFNN.Case study indicates that compared with those of the traditional grey theory and RBFNN models,the average relative deviation between predicted and the real value can decrease 5.4% based on the proposed model.


[1] 龙惟定,白玮,马素贞,等.中国建筑节能现状分析[J].建筑科学,2008,24(10):1-3.
Long Weiding,Bai Wei,Ma Suzhen,et al.Status analysis of building energy efficiency in China[J].Building Science,2008,24(10):1-3.
[2]Hygh J S,Decarolis J F,Hill D B,et al.Multivariate regression as an energy assessment tool in early building design[J].Building and Environment,2012,57:165-175.
[3]Ferreira P M,Ruano A E,Silva S,et al.Neural networks based predictive control for thermal comfort and energy savings in public buildings[J].Energy and Buildings,2012,55:238-251.
[4]Leephakpreeda T.Grey prediction on indoor comfort temperature for HVAC systems[J].Expert Systems with Applications,2008,34(4):2284-2289.
[6]Wang X,Chen Z,Yang C,et al.Gray predicting theory and application of energy consumption of building heat-moisture system[J].Building and Environment,1999,34(4):417-420.
[7]Wenbin H,Ben H,Changzhi Y.Building thermal process analysis with grey system method[J].Building and Environment,2002,37(6):599-605.
[8]Kumar U,Jain V.Time series models(Grey-Markov,Grey model with rolling mechanism and singular spectrum analysis)to forecast energy consumption in India[J].Energy,2010,35(4):1709-1716.
[10]Anstett M,Kreider J F.Application of neural networking models to predict energy use[J].Transactions—American Society of Heating Refrigerating and Air Conditioning Engineers,1993,99:505-510.
[11]Neto A H,Fiorelli F A S.Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption[J].Energy and Buildings,2008,40(12):2169-2176.
[12]Ekici B B,Aksoy U T.Prediction of building energy consumption by using artificial neural networks[J].Advances in Engineering Software,2009,40(5):356-362.
[13]Li Q,Ren P,Meng Q.Prediction model of annual energy consumption of residential buildings[A].Proceedings of the Advances in Energy Engineering(ICAEE)[C].Washing D C,USA:IEEE,2010.
[15]Deng Julong.Control problems of grey systems[J].Systems and Control Letters,1982,1(5):288-294.


Last Update: 2014-02-28