Integrating neural network and multimedia technologies to enhance college students’ career development

  • Lei Zhu Henan Vocational College of Tuina, Luoyang 471023, Henan, China
Keywords: multimedia technology; college students; career development; neural networks; knowledge fusion; learning algorithms
Article ID: 857

Abstract

Combining neural network technologies and computational techniques, this research establishes a career development promotion system based on a multi-modal neural network. It reveals that computer simulation technology and multimedia have positive intervention effects on college students’ career decision-making behaviors, similar to how biomolecular interactions regulate biological processes. This technology ensures scientific rigor, objectivity, and authenticity. A knowledge fusion algorithm, built on attributes and rules within the Hadoop platform and MapReduce parallel computing framework, facilitates effective data integration. Additionally, inspired by the regulatory mechanisms in biomolecular systems, a neural network-based algorithm, utilizing gradient descent, is applied to cultural learning, augmented by feedback analysis to assess students’ psychological changes, posture, and response dynamics during the learning process. To further optimize the career development framework, an Evolutionary Algorithm (EA) is used to enhance the performance of neural networks. Numerical simulations demonstrate the robustness of the proposed algorithm, achieving high accuracy (0.981), recall rate (1.0), and F-measure (0.997) in similarity computations. These results are particularly notable when biomechanic metrics, such as gesture and posture tracking, are integrated with linguistic data, such as spelling and vocabulary. The findings underscore that incorporating neural network insights into multimedia teaching methodologies can significantly enhance psychological motivation, behavioral adaptability, and engagement in college students, fostering improved educational outcomes and advancing interdisciplinary innovation in neural networks. It effectively enhances the internal driving force of “technology empowering psychological development” in the career planning system and provides a cognitive computing and biomechanic perspective for the construction of the smart education ecosystem.

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Published
2025-03-11
How to Cite
Zhu, L. (2025). Integrating neural network and multimedia technologies to enhance college students’ career development. Molecular & Cellular Biomechanics, 22(4), 857. https://doi.org/10.62617/mcb857
Section
Article