RETRACTED: Construction of smart sports platform in the background of healthy China

Fang, Hao

doi:10.1177/0020720920929663

Cited by 6 publications

(7 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is often used in sports wearable equipment, fitness equipment, fitness venues, and national fitness competitions [ 19 ]. In Figure 2 , compared to traditional fitness clubs, smart fitness uses IoT intelligent conventional fitness equipment, Internet data, and mobile terminals to achieve online and offline integration [ 20 – 22 ]. Users can use their mobile phones to scan the QR code or swipe the card to open the equipment for exercise.…”

Section: Methodsmentioning

confidence: 99%

The Design of Sports Games under the Internet of Things Fitness by Deep Reinforcement Learning

Wang

Liu²,

Sun

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

This study explores the application of deep reinforcement learning (DRL) in the Internet of Things (IoT) sports game design. The fundamentals of DRL are deeply understood by investigating the current state of IoT fitness applications and the most popular sports game design architectures. The research object is the ball return decision problem of the popular game of table tennis robot return. Deep deterministic policy gradients are proposed by applying DRL to the ball return decision of a table tennis robot. It mainly uses the probability distribution function to represent the optimal decision solution in the Markov Model decision process to optimize the ball return accuracy and network running time. The results show that in the central area of the table, the accuracy of returning the ball is higher, reaching 67.2654%. Different tolerance radii have different convergence curves. When r = 5 cm, the curve converges earlier. After 500,000 iterations, the curve converges, and the accuracy rate is close to 100%. When r = 2 cm and the number of iterations is 800,000, the curve begins to converge, and the accuracy rate reaches 96.9587%. When r = 1 cm, it starts to converge after 800,000 iterations, and the accuracy is close to 56.6953%. The proposed table tennis robot returns the ball in line with the requirements of the actual environment. It has practical application and reference value for developing IoT fitness and sports.

show abstract

Section: Methodsmentioning

confidence: 99%

The Design of Sports Games under the Internet of Things Fitness by Deep Reinforcement Learning

Wang

Liu²,

Sun

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Based on the selected reference samples, equation ( 27) is applied to carry out the association values between the samples to be evaluated as well as those used as references, i.e: 00 11 11…”

Section: ) Calculation Of Correlation Coefficientsmentioning

confidence: 99%

“…At present, in order to enhance the physical fitness of college students and curb the trend of continuous decline, colleges and universities have adopted the system to exert a certain pressure on students and implement the regulation of "physical test linked to graduation certificate" to encourage students to strengthen exercise and develop good exercise habits [9][10][11]. Therefore, exploring the construction of intelligent physical education teaching modes in colleges and universities by exploring new ideas of teaching reform may become a new way out for education in the new era [12][13].…”

Section: Introductionmentioning

confidence: 99%

Intelligent physical education teaching system in colleges and universities based on grey correlation degree model

Wei,

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

This paper first proposes the teaching model of college sports smart classrooms based on an online teaching platform and analyzes its basic structure and teaching process. Secondly, a gray correlation degree model is constructed for the teaching evaluation of the physical education SCT model, and the comparative sequence and reference sequence of the gray system are used to realize the solution of the correlation degree. Finally, the teaching quality evaluation index system of the physical education SCT model was constructed with SD University College of Physical Education, and the effectiveness of the application of physical education SCT model was analyzed. The results showed that the correlation degrees of a teacher teaching, student learning, environmental resources, and curriculum development were 0.317, 0.229, 0.225, and 0.266, respectively, and the physical education SCT model should focus on teaching methods and other aspects of consideration.

show abstract

“…At present, there is a lot of theoretical Research on the wisdom sports service for the elderly, and the research perspectives are gradually generalized, but the overall theoretical system has not yet matured [13][14][15]. The Research on the wisdom sports service for the elderly in China mainly focuses on the demographic transition, active aging, and wisdom aging as the background of the era and explores the wisdom of national fitness, wisdom aging service system, the integration of physical and medical synergy, the integration of community sports and aging service, the construction of wisdom community fitness center, and the integration of community sports and aging service, and the construction of wisdom community fitness center.…”

Section: Introductionmentioning

confidence: 99%

“…Jun Wang and Zhongwen Zheng. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] …”

mentioning

confidence: 99%

Exploring the Problems and Countermeasures in the Practice of Elderly Wisdom Sports Services in Anhui Province Based on Principal Component Analysis Methods

Wang,

Zheng

2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

With the continuous progress and broad application of cutting-edge information technology such as big data, cloud computing, virtual reality and artificial intelligence, senior sports services has ushered in unprecedented development opportunities, especially the rise of senior intelligent sports services. In this study, we applied the principal component analysis method to conduct in-depth screening of evaluation indexes to assess the quality of the practice of senior intelligent sports services in Anhui Province. Through the comprehensive analysis of the eigenroots and the contribution ratio of variance, this paper successfully identified the key factors and realized the effective dimensionality reduction of the data. Meanwhile, we adopted the logistic equation to accurately estimate the relevant parameters. Through the comprehensive analysis of eigenroot and variance contribution ratio, this paper successfully identifies the key factors, realizes the effective dimensionality reduction of the data, and adopts the logistic equation to accurately estimate the relevant parameters. The analysis results show that in the senior intelligent sports service index system, the highest weight value of platform is the operation and management platform, which reaches 0.4754. In the aspect of the demand for sports information of the seniors, the demand for online sports knowledge and skills is the highest, and the demand for online sports knowledge and skills is the highest. Regarding the demand for sports information of the elderly, the online acquisition of sports knowledge and skills has the highest demand of 203, followed by the demand for regular online sports knowledge lectures of 181. In the demand for outdoor bright trails, the elderly strongly want to enter their fitness and energy consumption data for evaluation, with a high degree of demand of 351. In addition, the demand for heart rate testing of the intelligent body testing station is the highest, with a degree of 186, followed by body fat testing, with a degree of 179. The Research in this paper not only focuses on the current situation and problems of intelligent sports services for the elderly, but also explores the methods and strategies to solve these problems, aiming to provide practical reference and guidance for the effective implementation of intelligent sports services for the elderly.

show abstract

RETRACTED: Construction of smart sports platform in the background of healthy China

Cited by 6 publications

References 2 publications

The Design of Sports Games under the Internet of Things Fitness by Deep Reinforcement Learning

The Design of Sports Games under the Internet of Things Fitness by Deep Reinforcement Learning

Intelligent physical education teaching system in colleges and universities based on grey correlation degree model

Exploring the Problems and Countermeasures in the Practice of Elderly Wisdom Sports Services in Anhui Province Based on Principal Component Analysis Methods

Contact Info

Product

Resources

About