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 Defect Analysis of Secondary Equipment Based on Power Dictionary and Apriori Algorithm

2021 ◽  
Vol 256 ◽  
pp. 02028
Author(s):  
Jinshuang Mu ◽  
Zhanjun Gao ◽  
Fengyuan Zhou
Keyword(s):  
Data Mining ◽  
Power System ◽  
Electric Power ◽  
Apriori Algorithm ◽  
Analysis Method ◽  
Analysis Model ◽  
Application Process ◽  
Equipment Operation ◽  
Processing Power ◽  
Key Characteristics

In order to improve the operation level and maintenance efficiency of the secondary equipment in the power system, based on the historical defect data, starting from the efficiency of data processing, power system need to build electricity dictionary. In the process of describing and processing the defect data, based on the electric power dictionary, the key characteristics of the defect data can be effectively extracted. From the perspective of data mining, this paper use Apriori algorithm to correlate and analyze the defect data, establish a analysis model for the secondary equipment defect data. Take a provincial electric power company’s secondary equipment historical defect data mining as an example, describes the application process and analysis method of Apriori algorithm. The results show that the algorithm can effectively dig out familial defects and find the weakness of the equipment, it has a certain guiding role for the improvement of equipment performance and secondary equipment operation, maintenance and overhaul.

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.

scholarly journals PO-088 Effect of Aerobic Exercise on Myocardial Mitochondria Fusion-Fission in Chronic Intermittent Hypoxia Mice

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Yulong Hu ◽  
Juan Chen
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Association Rules ◽  
Association Rule ◽  
Competitive Sports ◽  
Analysis Method ◽  
Mining Technology ◽  
Scientific Training ◽  
Biochemical Indicators ◽  
Analysis And Evaluation

Objective Training monitoring is an important part of scientific training, and also accumulated a large amount of data, but the analysis and evaluation of biochemical indicators are mostly concentrated on the level of experience and the general, phased and individualized research application of statistical methods. The data mining technology is applied to the analysis and evaluation of the biochemical indexes of competitive sports, the analysis of the data is carried out in the deep level, the potential, new and useful information and knowledge are extracted, and the new exploration ideas are carried out for the analysis of the biochemical indexes of competitive sports, and a more reliable and more powerful data branch is provided for the scientific and efficient training support. Methods Using the literature data method, logic analysis method and expert interview method, the application of the current data mining technology in the analysis of biochemical indicators is summarized. Results The scientific analysis and evaluation of athletes' physical function status has been the focus of domestic and foreign coaches and sports researchers. The application of data mining technology in sports biochemical indicators is also becoming more and more extensive. For example, Mao Jie and others applied the gray ART clustering model analysis method to the monitoring of competitive sports biochemical indicators. Through this data mining model, the coach can easily judge the athlete's competitive physical condition, and can provide a scientific basis for correct training according to the different competitive conditions of each athlete, using different training guidance programs and training methods. Ma Jing et al. explored the feasibility of applying decision tree algorithm and association rules in volleyball biochemical analysis. It was found that C5.0 decision tree and Apriori association rule algorithm can be used to predict and analyze the technical level of women's volleyball players. Li Guangjun and others successfully applied the association rule data mining to the biochemical data analysis of canoeists, and provided a basis for scientific decision-making and analysis of sports training and athlete selection. Zhang Hui designed a data mining system for sports biochemical index based on association rules. The results show that the system has fast data mining rate, short time consuming and high reliability. It provides a more scientific evaluation standard for the data mining of sports biochemical index, and also provides a basis for the future training program. Conclusions With the development of competitive sports, in order to achieve new heights, the application of data mining technology to vast biochemical data is of great significance for the establishment of scientific training evaluation methods and standards, and is also the inevitable development of future sports scientific research.

Management of Guidance and Counseling on Learning Discipline

2020 ◽  
Vol 10 (2) ◽  
pp. 60-74
Author(s):  
Muhammad Syauqi Mubarok
Keyword(s):  
Statistical Analysis ◽  
Descriptive Analysis ◽  
Field Studies ◽  
Guidance And Counseling ◽  
Analysis Method ◽  
Vocational High School ◽  
Analysis Model ◽  
Survey Techniques ◽  
Analysis Technique ◽  
Path Analysis Model

This article aims to examine and describe the influence of guidance and counseling management on learning discipline. The method used in this research is descriptive analysis method using survey techniques. Data collection techniques that used are documentation studies and field studies. Moreover, the data analysis technique that has been used to answer the research hypothesis is statistical analysis with a path analysis model. The location of the study was at the Ciledug Vocational High School Al-Musaddadiyah Garut, with 85 respondents taking part in the survey. The results of the discussion show that guidance and counseling management has a positive and significant effect on the discipline of learning

Sign in / Sign up

Export Citation Format

Share Document