scholarly journals Application of data mining technology and wireless network sensing technology in sports training index analysis

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Liqiu Qian ◽  
Jiatong Liu
Keyword(s):  
Data Mining ◽  
Wireless Network ◽  
Sports Training ◽  
Mining Technology ◽  
Index Analysis ◽  
Sensing Technology

Application of data mining technology and wireless network sensing technology in sports training index analysis

2020 ◽  
Author(s):  
Liqiu Qian ◽  
Jiatong Liu
Keyword(s):  
Data Mining ◽  
Test Accuracy ◽  
Analysis Method ◽  
Sports Training ◽  
Analysis Model ◽  
Data Types ◽  
Mining Technology ◽  
Accuracy Test ◽  
Index Analysis ◽  
Sensing Technology

Abstract The conventional analysis method can provide a general analysis of sports training index, but its ability is relatively low when analyzing niche data. To solve this problem, this paper proposes data mining technology. First, the indicator parameter classification is determined, then the data mining technology is imported, the sports training analysis mechanism is established through this technology, and the construction of the index analysis model is completed. The model is used to analyze the process of niche data mining, and effective data of training indicators are obtained. Deep learning is a method of machine learning based on representation of data.Through the coverage test, accuracy test and immunity test, the variable parameters of the comprehensive analysis capability are determined. Further calculation of this parameter shows that the comprehensive ability of the data mining application analysis method is improved by 37.14% compared with the conventional method, which is suitable for analysis of niche sports training indicators of different data types.

scholarly journals Application of Data Mining in the Guidance of Sports Training

2013 ◽  
Vol 765-767 ◽  
pp. 1518-1523
Author(s):  
Fan Hui Meng ◽  
Qing Li Li
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Experimental Data ◽  
Data Mining ◽  
Statistical Learning ◽  
Athletic Performance ◽  
Sports Training ◽  
Mining Technology ◽  
Broad Application ◽  
Use Of Data

Data mining is the techniques of finding the potential law from the data by machine learning and statistical learning .This paper focuses on a number of problems existed in the currents ports training, discusses the application principle of the data mining technology in sports training, and applies the critical neural networks for forecasting the performances of the athletes .Experimental data show that prediction of athletic performance by the use of neural network has very good approximation ability. It shows a broad application space of the use of data mining technology.

scholarly journals Sports Training System Based on Convolutional Neural Networks and Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yuwang Zhang ◽  
Yuan Zhang
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Convolutional Neural Network ◽  
Gait Recognition ◽  
Sports Training ◽  
Training Process ◽  
Mining Technology ◽  
Recognition Model ◽  
Network Algorithm ◽  
Neural Network Algorithm

In recent years, China’s sports industry has achieved good development, but the efficiency of athletes in the training process is difficult to have scientific guarantee. How to use scientific algorithm and data mining technology to accurately guide the sports training process has become a hot spot. Based on this, this paper studies the gait recognition model of sports training based on convolutional neural network algorithm. First, this paper analyzes the research status of gait recognition in the process of training and optimizes and improves the deficiencies in sports training. Then, the convolutional neural network algorithm and data mining technology are optimized and analyzed in the gait recognition model. Finally, the experimental results show that the convolutional neural network algorithm can realize the recognition and model reconstruction of athletes’ gait in the training process and can make the optimal strategy according to the gait differences of different athletes in the training process, and the recognition accuracy of athletes’ gait can reach more than 97%.

Research on the Guidance Methods of Sports Training Based on Data Mining Technology

2012 ◽  
Vol 155-156 ◽  
pp. 590-595
Author(s):  
Qian Zhou
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Data Mining ◽  
Statistical Learning ◽  
Athletic Performance ◽  
Sports Training ◽  
Mining Technology ◽  
Broad Application ◽  
Network Method ◽  
Scientific Nature

Data mining is use of machine learning, statistical learning from the data mining technology found in. In view of the current sports training problems, and discusses the data mining technology in the application of sports training theory, and through the key neural network method to forecast the athlete's performance in the application. The experimental data show that using neural network to predict athletic performance has a good approximation ability, but has good extension, which indicates that the use of the relevant data mining technology to guide the scientific nature of the sports training increases, will have broad application space.

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.

Framework and performance analysis of college English testing system based on data mining technology

2021 ◽  
pp. 1-11
Author(s):  
Liu Narengerile ◽  
Li Di ◽  
Keyword(s):  
Data Mining ◽  
Test System ◽  
Test Time ◽  
Testing System ◽  
Test Results ◽  
System Software ◽  
Examination System ◽  
Mining Technology ◽  
College English ◽  
And Performance

At present, the college English testing system has become an indispensable system in many universities. However, the English test system is not highly humanized due to problems such as unreasonable framework structure. This paper combines data mining technology to build a college English test framework. The college English test system software based on data mining mainly realizes the computer program to automatically generate test papers, set the test time to automatically judge the test takers’ test results, and give out results on the spot. The test takers log in to complete the test through the test system software. The examination system software solves the functions of printing test papers, arranging invigilation classrooms, invigilating teachers, invigilating process, collecting test papers, scoring and analyzing test papers in traditional examinations. Finally, this paper analyzes the performance of this paper through experimental research. The research results show that the system constructed in this paper has certain practical effects.

scholarly journals Mechanical equipment fault detection applying data mining technology

2020 ◽  
Vol 1684 ◽  
pp. 012024
Author(s):  
Yiqun Liu ◽  
Xiaogang Wang ◽  
Xiaoyuan Gong ◽  
Hua Mu
Keyword(s):  
Data Mining ◽  
Fault Detection ◽  
Mechanical Equipment ◽  
Mining Technology
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