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

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  • Meiling Dai
  • Yuxin Ding
  • Peibin Zhu
  • Lingxiao Xu

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.

Suggested Citation

  • Meiling Dai & Yuxin Ding & Peibin Zhu & Lingxiao Xu, 2026. "Effect of international new energy teaching on promoting regional new energy communication based on intelligent BP algorithm," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 48(7), pages 41-63.
    • Handle: RePEc:ids:ijgeni:v:48:y:2026:i:7:p:41-63
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