The construction of clients analysis system based on data mining technology

2012 ◽  
Author(s):  
Hui Zhang ◽  
Honghua Wang
Keyword(s):  
Data Mining ◽  
Mining Technology ◽  
Analysis System

scholarly journals Analysis of Characteristics of Tennis Singles Matches Based on 5G and Data Mining Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ming Li ◽  
Qinsheng Li ◽  
Yuening Li ◽  
Yunkun Cui ◽  
Xiufeng Zhao ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Statistical Methods ◽  
Analysis Data ◽  
Scientific Basis ◽  
Experimental Simulation ◽  
Mining Technology ◽  
Offensive Tactics ◽  
Analysis System ◽  
Scientific Decision

The level of technical and tactical decision-making in a tennis game has a very important impact on the outcome of the game. How to discover the characteristics and rules of the game from a large amount of technical and tactical data, how to overcome the shortcomings of traditional statistical methods, and how to provide a scientific basis for correct decision-making are a top priority. Based on 5G and association analysis data mining theory, we established a data mining model for tennis technical offensive tactics and association rules and conducted specific case studies. It can calculate the maximization and distribution rate of certain technologies, also distinguish between the athlete’s gain and loss rate and the spatial position on the track, and use artificial statistical methods to cause errors and subjective participation. This solution provides objective and scientific decision support for this problem and is used in the decision-making of the landing point in tennis match technology and tactics. Experimental simulation shows that the data mining technology analysis system used for regional tennis matches is more concise, efficient, and accurate than traditional movie analysis methods.

The Study of Score Analysis for Secondary School Based on Data Mining Technology

2011 ◽  
Vol 219-220 ◽  
pp. 396-399
Author(s):  
Shang Fu Hao ◽  
Zhi Qiang Zhang ◽  
Ying Hui Wei
Keyword(s):  
Data Mining ◽  
Score Distribution ◽  
Mining Technology ◽  
Factors Affecting ◽  
Architecture Model ◽  
Scientific Teaching ◽  
Score Analysis ◽  
Secondary Teaching ◽  
Using Data ◽  
Analysis System

Nowadays, the contents associated with deep score analysis is rarely involved in the existing secondary teaching management software, which is not conductive to fully develop the information implied by these data,without scientific teaching evaluation. Using data mining technology, multiple aspects of student score distribution will be shown accurately, identifying the regular factors affecting score changes. Standard score as the mathematical model is adopted in the system, choosing the standard SOA architecture model, and a scientific and efficient score analysis system based on JAVA, JSP is developed. The system provides decision support information for academic departments to promote better teaching work, and finally improve the quality of teaching.

Research on English score analysis system based on improved decision tree algorithm and fuzzy set

2020 ◽  
Vol 39 (4) ◽  
pp. 5673-5685
Author(s):  
Weiying Zhang
Keyword(s):  
Data Mining ◽  
Academic Performance ◽  
Student Performance ◽  
Reference Value ◽  
Mining Technology ◽  
Factors Affecting ◽  
Main Work ◽  
Score Analysis ◽  
Analysis System

At present, the data mining technology is introduced into the analysis of English scores, the data is deeply explored and analyzed reasonably, and the analysis results are used to guide the smooth development of teaching, which is conducive to improving the quality of English teaching. The main work of this thesis is based on the background of this study: taking the academic performance of college students as the application background, this paper first introduces the basic theoretical knowledge of data mining and the application status of data mining technology in education field. Secondly, this paper establishes a student performance database and uses data mining technology to carry out in-depth mining of the established performance database. Finally, the mining results are analyzed, and the factors affecting students’ academic performance are obtained. These analysis results have important reference value for the future improvement of teaching work in colleges and universities.

Design and Realization on the Financial Early-Warning Analysis System of Colleges and Universities Based on Data Mining Technology

2014 ◽  
Vol 623 ◽  
pp. 229-233 ◽  
Author(s):  
De Jiang Qi ◽  
Hai Yan Hu
Keyword(s):  
Data Mining ◽  
Early Warning ◽  
Financial Management ◽  
Financial Risk ◽  
Warning System ◽  
Colleges And Universities ◽  
Mining Technology ◽  
Id3 Algorithm ◽  
Financial Management System ◽  
Analysis System

In this thesis, in order to solve the student arrearage problems in colleges and universities, risk weight factor is introduced to improve ID3 algorithm through the research on data mining technology and the combination with financial management system of colleges and universities so that ID3 decision-making tree algorithm can classify based on the risk weights of all the factors of the financial data; the early warning system scheme on the student arrearage problems in colleges and universities is designed so as to predict the high-risk defaulting students dynamically and accurately and lay scientific foundations for avoiding financial risk in colleges and universities.

scholarly journals Data Mining-based Design and Implementation of College Physical Education Performance Management and Analysis System

2019 ◽  
Vol 14 (06) ◽  
pp. 87 ◽  
Author(s):  
Yimeng Fan ◽  
Yu Liu ◽  
Haosong Chen ◽  
Jianlong Ma
Keyword(s):  
Data Mining ◽  
Physical Education ◽  
Performance Management ◽  
Student Performance ◽  
Mining Technology ◽  
Development Platform ◽  
Sql Server 2005 ◽  
Analysis System ◽  
Education Performance ◽  
Architecture And Design

The purpose of this paper was to effectively apply data mining technology to sci-entifically analyze the students' physical education (PE) performance so as to serve the physical teaching. The methodology adopted in this paper was to apply ASP.NET 3-layer architecture and design and implement college PE performance management and analysis system under the premise of fully analyzing the system requirements based on Visual Studio2008 software development platform and using SQL Server 2005 database platform. Based on data mining technology, students' PE performances were analyzed, and decision tree algorithm was used to make valuable judgments on student performance. The results indicated that applying computer technology to the management and analysis of college PE per-formance can effectively reduce the teaching and managing workload of PE teachers so that the teachers concentrate more on the quality of physical educa-tion.

Advanced Statistical Tools for Improving Yield and Reliability

1999 ◽  
Author(s):  
Richard C. Kittler
Keyword(s):  
Data Mining ◽  
Analysis Data ◽  
Neural Nets ◽  
Future Trends ◽  
Statistical Tools ◽  
Mining Technology ◽  
Explanatory Variables ◽  
Data Coverage ◽  
Statistical Approaches ◽  
Adequate Data

Abstract Analysis of manufacturing data as a tool for failure analysts often meets with roadblocks due to the complex non-linear behaviors of the relationships between failure rates and explanatory variables drawn from process history. The current work describes how the use of a comprehensive engineering database and data mining technology over-comes some of these difficulties and enables new classes of problems to be solved. The characteristics of the database design necessary for adequate data coverage and unit traceability are discussed. Data mining technology is explained and contrasted with traditional statistical approaches as well as those of expert systems, neural nets, and signature analysis. Data mining is applied to a number of common problem scenarios. Finally, future trends in data mining technology relevant to failure analysis are discussed.

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