The Analysis of Combined Prediction Model of Building Energy Consumption with Grey Theory and RBF Neural Network

Yan Bai; Qing Chang Ren; Hong Mei Jiang

doi:10.4028/www.scientific.net/AMR.374-377.90

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 374-377The Analysis of Combined Prediction Model of...

The Analysis of Combined Prediction Model of Building Energy Consumption with Grey Theory and RBF Neural Network

Abstract:

A kind of new combined modeling method with GM(1,1) and RBNN (Radial Basis Neural Network) is brought forward, according to the idea that the method of neural network can bring grey prediction model a good modified effect. Based on the analysis of the energy consumption data of the existing and the annually-increased building area, the GM(1,1) model was then constructed. And the RBF neural network was used for the model residual error revising. The simulation and experiment results show that the novel model is more effective than the common grey model.

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Periodical:

Advanced Materials Research (Volumes 374-377)

Pages:

90-93

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.374-377.90

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Online since:

October 2011

Authors:

Yan Bai, Qing Chang Ren, Hong Mei Jiang

Keywords:

Building Energy Consumption, GM(1,1) Model, Radial Basis Neural Network

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