Proceedings of the 2019 International Conference on Management, Education Technology and Economics (ICMETE 2019)

Correlation Analysis of Energy Consumption and Industrial Structure in Transportation Industry-Taking Hebei Province as an Example

Authors
Xinyu Zhang
Corresponding Author
Xinyu Zhang
Available Online May 2019.
DOI
https://doi.org/10.2991/icmete-19.2019.28How to use a DOI?
Keywords
Industrial structure; Energy consumption; Correlation Analysis; Grey prediction
Abstract
Taking into account the impact of the proportion of industrial structure on the energy consumption of transportation industry, the gray correlation degree theory is applied to analyze the relationship among the energy consumption of the transportation industry in Hebei Province, the first, second and third industries, and the gray prediction GM (1,1). The model predicts the energy intensity of the transportation industry and other industries in Hebei Province in the next five years, and puts forward corresponding suggestions for the development of low-carbon transportation in Hebei Province.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2019 International Conference on Management, Education Technology and Economics (ICMETE 2019)
Part of series
Advances in Economics, Business and Management Research
Publication Date
May 2019
ISBN
978-94-6252-725-6
ISSN
2352-5428
DOI
https://doi.org/10.2991/icmete-19.2019.28How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xinyu Zhang
PY  - 2019/05
DA  - 2019/05
TI  - Correlation Analysis of Energy Consumption and Industrial Structure in Transportation Industry-Taking Hebei Province as an Example
BT  - 2019 International Conference on Management, Education Technology and Economics (ICMETE 2019)
PB  - Atlantis Press
SP  - 117
EP  - 120
SN  - 2352-5428
UR  - https://doi.org/10.2991/icmete-19.2019.28
DO  - https://doi.org/10.2991/icmete-19.2019.28
ID  - Zhang2019/05
ER  -