Open Access
Issue
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
Article Number 02048
Number of page(s) 5
Section Machine Learning and Energy Industry Structure Forecast Analysis
DOI https://doi.org/10.1051/e3sconf/202021402048
Published online 07 December 2020
  1. Zhou Changzhou. Research on the impact of scientific and technological innovation on the export competitiveness of high-tech products in China [J]. Science and technology innovation guide, 209, 16 (16) : 241 + 243. [Google Scholar]
  2. QIU Shilei, WU Zongjie, DONG Huizhong. Empirical Analysis on Factors of China’s High-tech Products Export一Based on VAR Model [J]. Science and Technology Management Research, 2017, 37(11): 105-111. [Google Scholar]
  3. Wang yu-nan. Empirical study on the impact of technological innovation on China’s high-tech exports[J]. Economic Research Guide, 2013 (23): 248-251+261. [Google Scholar]
  4. Shang Xiaoli. A Research on the Influential Factors of China’s High-tech Products Export[D]. Hebei University of Economics and Business, 2013. [Google Scholar]
  5. Wang Tiantian. The empirical evidence for the impact of high-tech industry agglomeration on the export trade in Jiangsu[D]. East China Normal University, 2013. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.