Research on Prediction Methods of Energy Consumption Data
Ning Chen1, Naernaer Xialihaer2,3, Weiliang Kong3, Jiping Ren2,3,*
Journal of New Media, Vol.2, No.3, pp. 99-109, 2020, DOI:10.32604/jnm.2020.09889
- 04 September 2020
Abstract This paper analyzes the energy consumption situation in Beijing, based
on the comparison of common energy consumption prediction methods. Here we
use multiple linear regression analysis, grey prediction, BP neural net-work
prediction, grey BP neural network prediction combined method, LSTM long-term
and short-term memory network model prediction method. Firstly, before
constructing the model, the whole model is explained theoretically. The advantages
and disadvantages of each model are analyzed before the modeling, and the
corresponding advantages and disadvantages of these models are pointed out.
Finally, these models are used to construct the Beijing energy forecasting model, More >