<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper firstly researches the role of sports in the cultivation of socialist core values in the context of healthy China, which is mainly embodied in the establishment of the correct goal to strive for in life and the establishment of a sense of fair and just social responsibility, and puts forward the path of socialist core values cultivation. Secondly, the socialist core values are studied by visualizing campus sports data. According to the LSTM neural network with good visualization and computational recognition ability, a campus sports data visualization model based on LSTM is constructed, and sensors are used to obtain the feature extraction of students’ sports. Based on the feature values, the feature state’s output value is computed using the LSTM neural network. Considering the extraction and feature loss problem in the calculation process, it is necessary to select a suitable loss function to optimize it and the example analysis of socialist core values based on LSTM data visualization. The results show that the higher the level of soccer skills, the higher the level of “self-confidence”, “strength”, “respect”, “responsibility”, “law-abiding” and “patriotism” indicators, the higher the level of “self-confidence” (t=3.736, p=0.005) indicators. The difference is significant. This study has contributed to socialist core values in the context of sports.</p>
</abstract>

This paper firstly researches the role of sports in the cultivation of socialist core values in the context of healthy China, which is mainly embodied in the establishment of the correct goal to strive for in life and the establishment of a sense of fair and just social responsibility, and puts forward the path of socialist core values cultivation. Secondly, the socialist core values are studied by visualizing campus sports data. According to the LSTM neural network with good visualization and computational recognition ability, a campus sports data visualization model based on LSTM is constructed, and sensors are used to obtain the feature extraction of students’ sports. Based on the feature values, the feature state’s output value is computed using the LSTM neural network. Considering the extraction and feature loss problem in the calculation process, it is necessary to select a suitable loss function to optimize it and the example analysis of socialist core values based on LSTM data visualization. The results show that the higher the level of soccer skills, the higher the level of “self-confidence”, “strength”, “respect”, “responsibility”, “law-abiding” and “patriotism” indicators, the higher the level of “self-confidence” (t=3.736, p=0.005) indicators. The difference is significant. This study has contributed to socialist core values in the context of sports.

Research on the Path of Cultivating Socialist Core Values through Campus Sports Data Visualization in the Context of Healthy China

Guangdong Business and Technology University

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper firstly researches the role of sports in the cultivation of socialist core values in the context of healthy China, which is mainly embodied in the...

Research on the Path of Cultivating Socialist Core Values through Campus Sports Data Visualization in the Context of Healthy China

Online veröffentlicht: 08. Nov. 2023

Seitenbereich: -

Eingereicht: 02. Feb. 2023

Akzeptiert: 19. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01046

Schlüsselwörter
LSTM neural network, Loss function, Data visualization model, Sports, Core values

© 2023 Xiaoling Xu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Path of Cultivating Socialist Core Values through Campus Sports Data Visualization in the Context of Healthy China

Online veröffentlicht: 08. Nov. 2023

Seitenbereich: -

Eingereicht: 02. Feb. 2023

Akzeptiert: 19. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01046

SchlüsselwörterLSTM neural network, Loss function, Data visualization model, Sports, Core values

© 2023 Xiaoling Xu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
LSTM neural network, Loss function, Data visualization model, Sports, Core values