Analysis Method of College Student Physical Education Quality Based on Big Data Analysis

2020 ◽  
pp. 576-581
Author(s):  
Chuncheng Wang
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
College Student ◽  
Physical Education ◽  
Big Data Analysis ◽  
Education Quality ◽  
Analysis Method

scholarly journals A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chengjun Zhou ◽  
DuanXu Wang
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Big Data ◽  
Data Analysis ◽  
College Student ◽  
Big Data Analysis ◽  
Technical Support ◽  
Assessment Process ◽  
Student Entrepreneurship ◽  
Study Results

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine (SVM) and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis.

scholarly journals A Big Data-Based Data Mining Tool for Physical Education and Technical and Tactical Analysis

2019 ◽  
Vol 14 (22) ◽  
pp. 220 ◽  
Author(s):  
Lili Pan
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Big Data ◽  
Data Analysis ◽  
Physical Education ◽  
Big Data Analysis ◽  
Competitive Sports ◽  
Data Mining Tool ◽  
Research Findings ◽  
Mining Tool

This paper attempts to develop a data mining tool to guide sports training, promote physical education and facilitate technical and tactical analysis. For this purpose, information techniques like mathematical statistics and big data analysis were employed to collect and analyse the information on competitive sports. Based on database and computer algorithm, the author designed a data mining tool applicable to the information of various competitive sports. The proposed tool can mine out valuable information from the big data, enabling trainers to realize targeted and efficient physical education. The mined information also helps improve the analysis of techniques and tactics of competitive sports. The research findings promote the application of information technology in physical education and competitive sports.

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