Open Access Article

Title: Effect of international new energy teaching on promoting regional new energy communication based on intelligent BP algorithm

Authors: Meiling Dai; Yuxin Ding; Peibin Zhu; Lingxiao Xu

Addresses: School of Marxism, Jimei University, Xiamen 361021, China ' School of Marxism, Jimei University, Xiamen 361021, China ' School of Ocean Information Engineering, Jimei University, Xiamen 361021, China ' Faculty of Arts and Science, University of Toronto (Mississauga), Toronto, L5L 1C6, Canada

Abstract: This study focuses on the application research of the intelligent Backpropagation (BP) algorithm in promoting regional new energy dissemination within international new energy teaching, exploring the practical value and mechanism of the algorithm from multiple dimensions. Based on the dataset of the Chinese Bridge Chinese Proficiency Competition for Foreign College Students and the learning data from the Chinese International Education Online platform, the study selects ten core features as input variables. They include learners' regional new energy cognitive basis, learning behaviour characteristics, and regional energy demand matching degree, while taking regional new energy dissemination effectiveness (covering knowledge mastery, dissemination willingness, and cooperative attitude) as the output variable to construct a BP neural network model. The research results enrich the theoretical system of international new energy education, and offer empirical support and practical guidance for designing regionally adaptive teaching programs and promoting the collaborative development of cross-border new energy technologies.

Keywords: new energy learning; BP algorithm; international new energy; new energy teaching; regional new energy communication.

DOI: 10.1504/IJGEI.2026.152144

International Journal of Global Energy Issues, 2026 Vol.48 No.7, pp.41 - 63

Received: 18 Nov 2025
Accepted: 30 Jan 2026
Published online: 09 Mar 2026 *

 

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