The teaching of sports science of track and field-based on nonlinear mathematical equations

Guan, Fuyu; Cao, Jingyan; Ren, Jie; Song, Wenli

doi:10.2478/amns.2021.2.00155

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…Deep learning analysis data method can predict and analyze the students' network thinking and behavior. Through mining and data to establish a deep learning model, it can realize the whole-process and full-sample analysis of individual students or groups, and realize personalized recommendation for innovation and reform [27][28]. We conduct online questionnaire surveys and statistical analysis through the following five aspects, is shown Table 1.…”

Section: Interaction Analysis Methods Of Ideological and Political Ed...mentioning

confidence: 99%

Research on Innovation of Daily Ideological and Political Education for College Students based on Deep Learning Model

Zhang¹,

Zhang²

2023

3C Tecnología

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Various network information is mixed, which has a great impact education, with continuous development informatization. However, development of informatization has provided convenience for the daily ideological political education, effectively solved time and space limitation daily ideological, and sustainable development. Therefore, positively influence formation of college students' noble morality. The informatization education resources can be effectively integrated, and the utilization rate resources improved. Information resources of ideological and political education, we propose a complete block diagram of the daily ideological system of college students. First, design a complete interactive analysis questionnaire for college student’s role of daily ideological and political education. Through questionnaire survey method, the survey and statistical weight scores were conducted to analyze the proportion of each indicator. Then, the framework of education in the network environment is adopted, which includes, class tutoring learning, class interactive learning, class in-depth study, process evaluation and feedback evaluation. Learn through a period of ideological and political education. Collect data as our training corpus. Finally, the training prediction model BERT-BiLSTM-CRF-based trained. Prediction of F1 BERT-BiLSTM- CRF -based can reach 91.09%.

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Section: Interaction Analysis Methods Of Ideological and Political Ed...mentioning

confidence: 99%

Research on Innovation of Daily Ideological and Political Education for College Students based on Deep Learning Model

Zhang¹,

Zhang²

2023

3C Tecnología

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show abstract

“…The training and test sets are split in a ratio of 4:1. The GRU network and LSTM network structure in the above models all use the same hyperparameters (the number of hidden layer neurons is 128, the sliding window is 6, the number of iterations is 400, and the batch_size is 256); the AM uses relu as the internal structure [33][34]. Activation function, and use Softmax function to normalize it; the convolution layer of CNN network is set to 64, the convolution kernel is 1, the maximum pooling layer is 4, and the dropout is 0.3; BP network adopts the number of hidden layer neurons is a network structure of 8; the SVM network adopts radial basis kernel function.…”

Section: Model Predictionsmentioning

confidence: 99%

Research on the development and application of CNN model in mobile payment terminal and blockchain economy

Liu¹

2023

3C Empresa

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As the most widely used payment method at this stage, mobile payment is more and more closely related to the blockchain economy. Traditional methods lack a certain degree of accuracy. This research proposes a feature-based and sequential-based Bilateral AM (BAM) and Convolutional Neural Network (CNN)-gated recurrent unit for the development and application of mobile payment and blockchain economy (Gated Recurrent Unit, GRU) hybrid model (BAM-CNN-GRU), select 5 feature parameters with high correlation with the blockchain for multivariate prediction. The introduction of BAM can automatically quantify the correlation between the input variables and the blockchain, and strengthen the expression of historical key information on the predicted output; the introduction of CNN can extract high-dimensional features that reflect the non-stationary dynamic changes of the blockchain. The proposed hybrid model achieves good results in both single-step and multi-step long-term series and multivariate input blockchain prediction. Compared with the other six methods, MAE is reduced by 75.45%, 64.74%, 62.84%, respectively. 59.41%, 45.54%, 44.16%. Compared with the BAM-GRU model, the CNN-GRU model, the GRU model, the LSTM model, the support vector machine SVM model and the BP model, the prediction accuracy of the hybrid model has been greatly improved, and it has a broader application prospect.

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“…On the environmental monitoring website, the data of natural and, socio-economic influencing factors of the target city in the last year were counted to analyze and study the spatial and temporal distribution pattern of heavy haze weather [31][32][33]. The spatial distribution state of particulate matter concentrations in a year was analyzed based on the PM2.5 and PM10 concentrations counted in the city throughout the year [34][35]. Figure 1 is made based on the quarterly averages of PM2.5 and PM10 concentrations of polluting particulate matter at eight monitoring sites in the city throughout the year related to heavy haze weather, using spatial interpolation with GIS technology.…”

Section: Characteristics Of Spatial and Temporal Distribution Of Heav...mentioning

confidence: 99%

Effects of outdoor volleyball exercise on cardiorespiratory function under a heavy haze environment

Wang

2023

3C TIC

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Haze has been one of the originators of the impact on human health. It is noteworthy that all functions of the human body can decline or even fail in a heavy haze environment. In this paper, the environmental monitoring website was used to count the data of meteorological and other natural factors as well as socio-economic influencing factors in the target cities over the past year. On this basis, the spatial and temporal distribution patterns of heavy haze weather were analyzed and studied. For the 100 volunteers who had been exposed to heavy haze pollution for a long time, the physical activity time of volleyball was classified into four levels using the quadratic method. Apart from that, a mixed linear model with fixed and random effects was constructed to explore the effects on cardiorespiratory fitness after outdoor volleyball exercise under a heavy haze environment. According to the model analysis results, the outdoor volleyball exercise had a significant interaction effect on pulmonary ventilation function in men only. Moreover, volleyball could be beneficial to the target group when the physical activity had not yet reached the level of high-level volleyball physical activity. This resulted in an improvement of 0.2L, 0.04L, 1.19%, and 0.03L in their pulmonary ventilation function indexes, respectively. However, the negative effects of a heavy haze environment were heavier after reaching a high-level degree. In addition, the indicator kept decreasing, from 2.04L, 1.13L, 63.63%, 1.99L to 1.98L, 1.04L, 60.78%, and 1.83L, respectively.

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The teaching of sports science of track and field-based on nonlinear mathematical equations

Cited by 4 publications

References 10 publications

Research on Innovation of Daily Ideological and Political Education for College Students based on Deep Learning Model

Research on Innovation of Daily Ideological and Political Education for College Students based on Deep Learning Model

Research on the development and application of CNN model in mobile payment terminal and blockchain economy

Effects of outdoor volleyball exercise on cardiorespiratory function under a heavy haze environment

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