scholarly journals Design of real-time data analysis system for physical training based on data mining technology

2021 ◽  
Vol 1982 (1) ◽  
pp. 012206
Author(s):  
Deng Hui ◽  
Wang Jin
2001 ◽  
Vol 7 (S2) ◽  
pp. 1164-1165
Author(s):  
P-G Åstrand ◽  
S. Csillag

Recent developments in detector technology [1] for EELS and Energy Filtered TEM has made possible to obtain large number of spectra and energy filtered images during very short exposure times. This in turn opens the exciting possibility of studying time dependent processes in the electron microscope, during exposure to the electron beam as well as the study of different radiation sensitive samples which are being degraded during lengthily data recording. This kind of data recording generates a large amount of data and manual data analysis should be avoided in order to be able to fully benefit from the improved sensitivity and increased speed of these new detectors. Thus a fast, real-time data analysis system is highly desirable.A system for real-time data analysis (spectra classification) of data generated from such a detector has been simulated in a program based on the object oriented C++ framework ROOT [2][3].


2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.


2021 ◽  
Vol 13 (0203) ◽  
pp. 78-81
Author(s):  
Ashish P. Joshi ◽  
Biraj V. Patel

The model and pattern for real time data mining have an important role for decision making. The meaningful real time data mining is basically depends on the quality of data while row or rough data available at warehouse. The data available at warehouse can be in any format, it may huge or it may unstructured. These kinds of data require some process to enhance the efficiency of data analysis. The process to make it ready to use is called data preprocessing. There can be many activities for data preprocessing such as data transformation, data cleaning, data integration, data optimization and data conversion which are use to converting the rough data to quality data. The data preprocessing techniques are the vital step for the data mining. The analyzed result will be good as far as data quality is good. This paper is about the different data preprocessing techniques which can be use for preparing the quality data for the data analysis for the available rough data.


2015 ◽  
Vol 740 ◽  
pp. 351-354
Author(s):  
Feng Li ◽  
Hong Bin Wang ◽  
Dao Jun Deng ◽  
Yan Xia Zhang

This paper mainly discusses the applications of real-time data mining technology in fault prediction of power plant generator. Massive real-time historical data of thermal power plant turbine generator equipment is stored to realize comprehensive quantitative assessment of thermal power plant turbine generator’s online security status and potential failure Early Warning. It is based on the Real-time data mining analysis and modeling techniques.


2018 ◽  
Vol 19 (S18) ◽  
Author(s):  
Ahmed Sanaullah ◽  
Chen Yang ◽  
Yuri Alexeev ◽  
Kazutomo Yoshii ◽  
Martin C. Herbordt

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