Abstract: Using BP neural network in past to predict the energy consumption of the building resulted in some shortcomings. Aiming at these shortages, a new algorithm which combined genetic algorithm with Levenberg-Marquardt algorithm (LM algorithm) was proposed. The proposed algorithm was used to improve the neural network and predict the energy consumption of buildings. First, genetic algorithm was used to optimize the weight and threshold of Artificial Neural Network (ANN). Levenberg-Marquardt algorithm was adopted to optimize the neural network training. Then the predicting model was set up in terms of the main effecting factors of the energy consumption. Furthermore, a public building power consumption data for one month is collected by establishing a monitoring platform to train and test the model. Eventually, the simulation result proved that the proposed model was qualified to predict short-term energy consumption accurately and efficiently.

Dinghao Lv, Bocheng Zhong and Jing Luo, “Application of GLBP Algorithm in the Prediction of Building Energy Consumption” International Journal of Advanced Computer Science and Applications(IJACSA), 6(6), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060607

@article{Lv2015,
title = {Application of GLBP Algorithm in the Prediction of Building Energy Consumption},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060607},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060607},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {6},
author = {Dinghao Lv and Bocheng Zhong and Jing Luo}
}