scholarly journals Application of Data Mining Technology in Analyzing the Impact of Mileage on Unqualified Rate of Vehicle Emission Inspection

2019 ◽  
Vol 300 ◽  
pp. 032085
Author(s):  
Van Tuu Nguyen ◽  
Jiangwei Chu
Keyword(s):  
Data Mining ◽  
Vehicle Emission ◽  
Mining Technology ◽  
The Impact

scholarly journals Influence of Healthy Physical Fitness on the Teaching of Aerobics Course Based on Big Data Mining Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Laipeng Xiao
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Physical Fitness ◽  
Physical Training ◽  
Body Shape ◽  
Teaching Experiment ◽  
The Body ◽  
Mining Technology ◽  
Big Data Mining ◽  
The Impact

Healthy physical fitness is one of the hot topics discussed by scholars at home and abroad in recent years, and it is a key indicator for evaluating students’ physical function and body shape. Aerobics, also known as bodybuilding, means that the body and health of students should have a better promotion effect, but in reality, many students found that after elective aerobics, body shape and health level basically did not improve, which is related to the setting of aerobics courses, especially the lack of physical training. Aerobics and other sports have common requirements in physical training, such as strength quality, speed quality, endurance quality, agility quality, and flexibility quality. This article is aimed at studying the impact of healthy physical fitness based on big data mining technology on the teaching of aerobics. On the basis of analyzing the process of data mining, the composition of healthy physical fitness, and the role of aerobics, it is used to test students in a certain university through experimental methods and statistical methods. Carry out aerobics teaching experiment, and compare and analyze the data measured by the experimental samples. The experimental results show that the use of healthy physical fitness in aerobics teaching can effectively promote the learning and improvement of aerobics skills.

scholarly journals The Impact of Entrepreneurship Education of Entrepreneurs on the Entrepreneurial Psychology of Sports Majors From the Perspective of Pedagogy

2021 ◽  
Vol 12 ◽  
Author(s):  
Taofeng Liu ◽  
Mariusz Lipowski ◽  
Yingying Xue ◽  
Tao Xiao ◽  
Hongzhen Liu ◽  
...  
Keyword(s):  
Data Mining ◽  
Influencing Factors ◽  
Entrepreneurship Education ◽  
Behavior Control ◽  
Entrepreneurial Behavior ◽  
Tree Model ◽  
Mining Technology ◽  
Sports Industry ◽  
National Training ◽  
The Impact

In recent years, with the continuous reform and innovation of the sports industry, the national training of sports talents has gradually developed into the training mode of skilled sports talents and professional talents in the field of sports. Therefore, the research on the influence of entrepreneurship education on the entrepreneurial psychology of sports majors has become the inevitable requirement of the development of the sports industry. The purposes are to understand the entrepreneurial psychology and its influencing factors of the students in sports majors after graduation and promote more suitable college students to start businesses and realize self-value. With the students in sports majors in four colleges of Y province as the research object, the typical model in psychology, planning behavior model, is taken as the basic theoretical basis. The questionnaire method combined with the data mining technology based on the decision tree model is adopted to study the influencing factors of entrepreneurial psychology of sports majors. It focuses on the influencing factors and mechanisms of the entrepreneurial drive of sports students. The results show that the three factors, namely, entrepreneurial behavior attitude, entrepreneurial subjective norms, and entrepreneurial perceptual behavior control, are different and interrelated. They are inseparable and can be transformed into each other under certain conditions. Three factors jointly drive the entrepreneurial behavior of students in sports majors. The entrepreneurial drive of students in sports majors in Y province is a dynamic system mechanism, which is analyzed using data mining technology. The entrepreneurial perceptual behavior control is the core factor affecting the entrepreneurial drive of students in sports majors. However, the success rate of entrepreneurs will be higher when the three elements play a reasonable role. The subjective factors driving their entrepreneurship will be reduced in direct proportion when entrepreneurs are deficient in one aspect.

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.

scholarly journals Multi-GPU approach to global induction of classification trees for large-scale data mining

2021 ◽  
Author(s):  
Krzysztof Jurczuk ◽  
Marcin Czajkowski ◽  
Marek Kretowski
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Real Life ◽  
Population Based ◽  
Tree Structure ◽  
Global Approach ◽  
Data Parallel ◽  
Large Scale Data ◽  
The Impact ◽  
Scale Data

AbstractThis paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers. It searches for the tree structure and tests simultaneously and thus gives improvements in the prediction and size of resulting classifiers in many situations. However, it is the population-based and iterative approach that can be too computationally demanding to apply for big data mining directly. The paper demonstrates that this barrier can be overcome by smart distributed/parallel processing. Moreover, we ask the question whether the global approach can truly compete with the greedy systems for large-scale data. For this purpose, we propose a novel multi-GPU approach. It incorporates the knowledge of global DT induction and evolutionary algorithm parallelization together with efficient utilization of memory and computing GPU’s resources. The searches for the tree structure and tests are performed simultaneously on a CPU, while the fitness calculations are delegated to GPUs. Data-parallel decomposition strategy and CUDA framework are applied. Experimental validation is performed on both artificial and real-life datasets. In both cases, the obtained acceleration is very satisfactory. The solution is able to process even billions of instances in a few hours on a single workstation equipped with 4 GPUs. The impact of data characteristics (size and dimension) on convergence and speedup of the evolutionary search is also shown. When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.

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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