Title: Research on sustainable development, innovation and entrepreneurship transformation needs of key energy industries

Authors: Liang Tang

Addresses: School of Education, Shanghai Normal University, Shanghai, 200234, China; Student Affairs Office, Jiangsu University of Science and Technology, Zhenjiang, 212000, China

Abstract: In order to improve the sustainable development ability of the energy industry, the artificial intelligence algorithm is introduced into the sustainable development prediction, the sustainable development evaluation model of L-M improved BP neural network is proposed, and the grey prediction model is used to predict the transformation demand. The algorithm simulation shows that the fitting degree between the L-M improved BP neural network and the expected value of experts in the evaluation of sustainable development has reached 0.98. In addition, the prediction performance test of the grey prediction model shows that its prediction accuracy has reached 99.4%. The above results show that it is effective to use L-M improved BP neural network to evaluate the sustainable development of the energy industry, which can help the energy industry understand the current development status.

Keywords: energy industry; sustainable development; transformation needs; improved BP neural network; gray prediction.

DOI: 10.1504/IJISD.2024.140843

International Journal of Innovation and Sustainable Development, 2024 Vol.18 No.5/6, pp.669 - 685

Received: 22 Jun 2022
Accepted: 25 Oct 2022
Published online: 03 Sep 2024 *

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