| Issue |
E3S Web Conf.
Volume 275, 2021
2021 International Conference on Economic Innovation and Low-carbon Development (EILCD 2021)
|
|
|---|---|---|
| Article Number | 02040 | |
| Number of page(s) | 6 | |
| Section | Green Low-Carbon and Energy Saving and Emission Reduction Applications | |
| DOI | https://doi.org/10.1051/e3sconf/202127502040 | |
| Published online | 21 June 2021 | |
GDP forecast of accommodation and catering industry in X city based on multi variable grey model —— Energy saving development of accommodation and catering industry
1
Qian Gao, State Grid Jiangsu Electric Power, Nanjing City, China
2
Yunyun Liu, State Grid Suqian Power Supply Company, Suqian City, China
3
Junyi Yang, State Grid Jiangsu Electric Power, Nanjing City, China
4
Yu Hong, State Grid Jiangsu Electric Power, Nanjing City, China
5
Lei Wen, Southeast University, Nanjing City, China
* Qian Gao: 15105181322@139.com
As the GDP of lodging and catering industry is generally quarterly or annual, the data volume is very small, so it is difficult to accurately predict the GDP of lodging and catering industry in this city for a city. However, a city can accurately predict the GDP development of the lodging and catering industry through electricity consumption. And the local government can formulate relevant policies to promote the stable development of lodging and catering industry and economy, and find the relationship between electricity consumption and GDP development of this industry, so as to achieve the purpose of low energy consumption and fast economic growth.t. This paper first conducted desensitization and normalization processing on the data, and then used Matlab to forecast the GDP of the lodging and catering industry in X City respectively by using GM (1, N) grey model, multiple linear regression model and BP neural network model. The experimental results show that the GM (1, N) grey model is more accurate and reliable than the other two methods in the case of less data. This paper solves the problem that the GDP of accommodation and catering industry in a single city is inaccurate.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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