Article: Construction of implementation system for vocational education targeted training model based on BP neural network under the integration of industry and education Journal: International Journal of Data Science (IJDS) 2025 Vol.10 No.7 pp.256 - 269 Abstract: Industry-education integration has become a pivotal national strategy in China, yet its complex interactions are difficult to capture with traditional models, which often rely on empirical methods lacking precision. To address this gap, this study introduces a BP neural network-based evaluation approach. By iteratively adjusting neuron weights to fit nonlinear functions, the method enables accurate assessment of industry-education integration. The research highlights the importance of vocational education, identifies key challenges, and explores its role in China's educational system. A neural network model is built using 10 secondary indicators, with simulation and validation performed in MATLAB on real-world data. Results show strong dynamic tracking and fitting accuracy, providing a scientific basis for precise evaluation. This study contributes an innovative data-driven method for optimising vocational training models and offers valuable insights for policy development and system improvement. Inderscience Publishers - linking academia, business and industry through research

Title: Construction of implementation system for vocational education targeted training model based on BP neural network under the integration of industry and education

Authors: Shunji Wang

Addresses: Office of Academic Affairs, Changchun Finance College, Jilin, Changchun, 130000, China

Abstract: Industry-education integration has become a pivotal national strategy in China, yet its complex interactions are difficult to capture with traditional models, which often rely on empirical methods lacking precision. To address this gap, this study introduces a BP neural network-based evaluation approach. By iteratively adjusting neuron weights to fit nonlinear functions, the method enables accurate assessment of industry-education integration. The research highlights the importance of vocational education, identifies key challenges, and explores its role in China's educational system. A neural network model is built using 10 secondary indicators, with simulation and validation performed in MATLAB on real-world data. Results show strong dynamic tracking and fitting accuracy, providing a scientific basis for precise evaluation. This study contributes an innovative data-driven method for optimising vocational training models and offers valuable insights for policy development and system improvement.

Keywords: industry-education integration; BP neural network; vocational education; oriented training; system construction.

DOI: 10.1504/IJDS.2025.151191

International Journal of Data Science, 2025 Vol.10 No.7, pp.256 - 269

Received: 08 Nov 2024
Accepted: 21 Jan 2025
Published online: 16 Jan 2026 *

Title: Construction of implementation system for vocational education targeted training model based on BP neural network under the integration of industry and education

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