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Parallel Integration Method of Physical Education Information Based on Multi Machine Learning Model

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e-Learning, e-Education, and Online Training (eLEOT 2023)

Abstract

Physics education is one of the important subjects to cultivate students' Scientific literacy and innovation ability. However, the traditional physics education lacks personalized and diversified teaching methods. At the same time, the conventional parallel integration methods of physics education information usually only focus on the integration of decision-making information, ignoring the parallel integration link, resulting in poor integration effect.Therefore, a parallel integration method of physical education information based on multi machine learning model is designed. Extracting physical education information and integrating the feature of elements, machine learning and classifying multiple physical education information. Based on the multi machine learning model, the integration and transmission mechanism of physical education information is measured, the physical education information and data are transferred in a two-way way, and the physical information flow is integrated and managed in a parallel integration mode, so as to realize the parallel integration of physical education information. The simulation experiment verifies that the integration method has better integration effect and can be applied in real life.

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Aknowledgement

2022 Hubei Provincial Department of Education Science and Technology Research Plan Project (B2022315).

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Correspondence to Han Xu .

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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Chen, Q., Xu, H. (2024). Parallel Integration Method of Physical Education Information Based on Multi Machine Learning Model. In: Gui, G., Li, Y., Lin, Y. (eds) e-Learning, e-Education, and Online Training. eLEOT 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 546. Springer, Cham. https://doi.org/10.1007/978-3-031-51503-3_19

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  • DOI: https://doi.org/10.1007/978-3-031-51503-3_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-51502-6

  • Online ISBN: 978-3-031-51503-3

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