Abstract
With the continuous increase of China's total energy consumption, we can find the rule and grasp its development trend from the change trend of energy consumption. In order to provide scientific basis for rational use of energy. In this paper,firstly, based on the data of total energy consumption of shandong province from 2007 to 2016, grey prediction model and BP neural network were used to predict total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted value of each year and the average relative error of the two models was 7.25% and 3.70% respectively. Secondly, on the basis of the grey prediction model, BP neural network was used to correct the predicted value of total energy in shandong province. Then, the grey BP modified model was used to obtain the total energy consumption of shandong province from 2007 to 2016. MATLAB was used to calculate the predicted values of each year and the average relative error of the modified model was 2.04%. Finally, the total energy consumption of shandong province in 2018-2035 is predicted. The results show that the average relative error is small and the prediction effect is obvious. This shows that the grey BP model is effective in predicting total energy consumption.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Energy and Power Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.