Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

December 13, 2023


Pages


DOI

Article

Research on the Synergistic Development and Operation Mechanism of Vocational Education and Innovative Development Concepts in the Context of Deep Learning

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Authors

Qingshan Xiao Affiliation:
Hunan Vocational College of Engineering, Changsha, Hunan, 410151, China.


Abstract

This paper proposes that the synergistic mechanism promotes the vocational education innovation system to transition from the primitive low-level, ordered and relatively balanced stage to the high-level, ordered and fully synergistic stage. By analyzing the dynamic evolution process of the order parameter, a complex system with self-evolution capability is built, and the vocational education collaborative innovation model is constructed at three levels: macro, meso and micro. Finally, in carrying out the benefit distribution and arithmetic example analysis, the spillover effect of the synergistic subject is explored, and the optimal value is taken using the optimization model of synergistic development of higher vocational colleges and universities. The results show that when the quadratic term coefficient of innovation output is 0.086, the stabilization strategy is (0,1) or (1,0), and the multi-body innovation resources realize interaction stabilization without spillover or feedback effects. This study proposes the optimal path of innovation integration mechanism from the aspects of mechanism, mode and content, which can provide new ideas for the collaborative development of vocational education and enterprises.


Keywords

Ordinal covariates, Dynamic evolution, Spillover effects, Synergistic development optimization, Optimal generation values, 97B10


Citation

Xiao, Q. (2023). Research on the synergistic development and operation mechanism of vocational education and innovative development concepts in the context of deep learning. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01482
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