Current situation and development direction of sports industry in colleges and universities based on euclidean algorithm

Ma, Shunjiang; Liu, Gaicheng; Huang, Zhiwu

doi:10.3233/jifs-219032

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…It is proposed that AFSA is used to solve the path problem of the vehicle with return trip, which can reflect the individual performance function of artificial fish and the three classic behaviors of artificial fish: foraging, clustering and rear-end pursuit, all of which are applied to the path optimization problem [22]. The artificial fish swarm algorithm is combined with the nuclear fuzzy C-means algorithm, and has been successfully applied to wine quality classification [23]. A cluster analysis algorithm based on artificial fish swarm algorithm is proposed and successfully applied to regional economic analysis [24].…”

Section: Related Workmentioning

confidence: 99%

Research on Adaptive Intelligent Decision Algorithm in Industry 4.0 Digital Economy and Management Transformation Based on Clustering Algorithm

2024

Teh. vjesn.

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How to transform the business model of enterprises and make it more in line with the new requirements of industrial upgrading is an important part of the government's supply-side reform in the era of Industry 4.0. For the current research on the good management transformation of digital economy in the fourth Industrial revolution, linear function and four commonly used nonlinear function models are first selected to test the good management transformation of digital economy in different technologies, and the key success factors of the strategic transformation from traditional industry to Industry 4.0 business model are explored based on fuzzy hierarchical analysis. Logistic and Gompertz models were used to judge the life cycle stage of the hot technologies of the fourth Industrial revolution, and based on their development trend clustering, the hot technology groups of the fourth Industrial revolution were explored. Secondly, k-means clustering algorithm based on the optimal class center perturbation is proposed, and simulation experiments are carried out. A clustering algorithm based on k-means algorithm is designed, and the moving mode of k-means in the algorithm is changed, and a disturbance strategy is added to strengthen the adaptive intelligent decision-making ability of the algorithm. K-means clustering algorithm based on the optimal class center disturbance is proposed, and simulation experiments are conducted. At the same time, the values of step size factors in the algorithm are compared experimentally. Finally, it explores the function mechanism of digital economy, management transformation and management transformation in the operation of supply chain node enterprises. By analyzing the current situation and problems of digital operation of logistics and supply chain enterprises, it constructs the digital operation system of supply chain enterprises, and proposes the path of digital transformation and upgrading of supply chain enterprises, so as to promote the rapid development of supply chain node enterprises.

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Section: Related Workmentioning

confidence: 99%

Research on Adaptive Intelligent Decision Algorithm in Industry 4.0 Digital Economy and Management Transformation Based on Clustering Algorithm

2024

Teh. vjesn.

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“…Competitive sports, for example, have generated substantial amounts of data, presenting new opportunities for advancement. By collecting and calculating the game data to establish a simulation database, the team can provide the best tactics [4][5]. 2, the current proportion of the population participating in sports in China stands at 40%.…”

Section: Introductionmentioning

confidence: 99%

Research on the Development Path of Traditional Minority Sports Industry under the Background of Big Data

Yu,

Li,

Zhao

2023

Proceedings of the 4th International Conference on Modern Education and Information Management, ICMEIM 2023, September 8–10, 20

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To comprehensively explore the evolution of niche sports within the larger sports industry landscape, we present a research initiative focused on the trajectory of minority sports development, specifically in the context of big data utilization. This document aims to assess the current state of China's sports industry, pinpoint opportunities for harmonizing supply and demand dynamics in the market, foster collaborative efforts for sports advancement, and unearth and nurture key players in China's sports sector. Additionally, this research seeks to delve deeper into understanding user requirements and values, advocate for the integration of big data in sports competitions, and fortify innovative strategies within the sports industry. Currently, the development of traditional ethnic minority sports is faced with diversity, economic and profit implications. In the construction of the Chinese dream, the development of minority sports should be scientific, ecological and secular.

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“…The sports industry's specificity and complexity require a reasonable adjustment and upgrade of its structure to achieve long-term sustainable economic growth. By studying the inner law of the structural change of the sports industry, a reasonable industrial layout and development direction can be revealed so as to promote the optimal allocation of resources and the improvement of economic efficiency and to promote the development and upgrading of the sports industry [7][8]. Therefore, an in-depth study of the relationship between structural upgrading of the sports industry and economic growth is of great significance for promoting the development of the sports industry and facilitating economic growth.…”

Section: Introductionmentioning

confidence: 99%

The Relationship between Structural Upgrading and Economic Growth of Sports Industry Based on AD-AS Modeling

Wang

2023

Applied Mathematics and Nonlinear Sciences

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This paper determines the structural upgrading measurement indexes of the sports industry by analyzing the metrics from three perspectives: industrial structure advancement, rationalization, and coordination. With reference to the AD-AS model in economics, it introduces the positive exchange factor to improve the comprehensive supply model, utilizes the pressure factor and the negative exchange factor to improve the comprehensive supply-demand model, and obtains the improved SAD-SAS model. Based on the equilibrium relationship between aggregate supply and aggregate demand, five hypotheses regarding influence are proposed. The results show that the output growth rate fluctuation coefficient of the sports industry is 0.25-0.45, and the time, robust, and spatial elasticity economic growth volume shows a stable incremental curve with the incremental increase of time, which illustrates that the structural upgrading of the sports industry and the economic growth is a positive effect significant relationship.

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Current situation and development direction of sports industry in colleges and universities based on euclidean algorithm

Cited by 6 publications

References 2 publications

Research on Adaptive Intelligent Decision Algorithm in Industry 4.0 Digital Economy and Management Transformation Based on Clustering Algorithm

Research on Adaptive Intelligent Decision Algorithm in Industry 4.0 Digital Economy and Management Transformation Based on Clustering Algorithm

Research on the Development Path of Traditional Minority Sports Industry under the Background of Big Data

The Relationship between Structural Upgrading and Economic Growth of Sports Industry Based on AD-AS Modeling

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