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data processing of small samples based on grey distance information approach

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Journal of Systems Engineering and Electronics 2007年第2期18卷 281-289页

作者： Ke Hongfa, Chen Yongguang & Liu Yi 1. Coll. of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, P. R. China 2. Unit 63880, Luoyang 471003, P. R. China Coll. of Electronic Science and Engineering National Univ. of Defense Technology Changsha 410073 P.R. China Unit 63880 Luoyang 471003 P.R. China

data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

关键词： data processing Grey theory Norm theory, Small samples Uncertainty assessments Grey distance measure, Information whitening ratio.

data processing Model of Coalmine Gas Early-Warning System

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Journal of China University of Mining and Technology 2007年第1期17卷 20-24页

作者： QIAN Jian-sheng YIN Hong-sheng LIU Xiu-rong HUA Gang XU Yong-gang School of Information and Electrical Engineering China University of Mining ＆ Technology Xuzhou Jiangsu 221008 China Library of China University of Mining ＆ Technology Xuzhou Jiangsu 221008 China

The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.

关键词： gas early-warning data processing queuing theory priority model high efficiency

A machine learning framework for low-field NMR data processing

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Petroleum Science 2022年第2期19卷 581-593页

作者： Si-Hui Luo Li-Zhi Xiao Yan Jin Guang-Zhi Liao Bin-Sen Xu Jun Zhou Can Liang College of Artificial Intelligence and College of Petroleum Engineering China University of PetroleumBeijing102249China China National Logging Corporation Xi©anShaanxi 710076China Changzhou Institute of Technology ChangzhouJiangsu213000China

Low-field(nuclear magnetic resonance)NMR has been widely used in petroleum industry,such as well logging and laboratory rock core ***,the signal-to-noise ratio is low due to the low magnetic field strength of NMR tools and the complex petrophysical properties of detected *** the noise and highlighting the available NMR signals is very important for subsequent data *** denoising methods are normally based on fixed mathematical transformation or handdesign feature selectors to suppress noise characteristics,which may not perform well because of their non-adaptive performance to different noisy *** this paper,we proposed a“data processing framework”to improve the quality of low field NMR echo data based on dictionary *** learning is a machine learning method based on redundancy and sparse representation *** information in noisy NMR echo data can be adaptively extracted and reconstructed by dictionary *** advantages and application effectiveness of the proposed method were verified with a number of numerical simulations,NMR core data analyses,and NMR logging data *** results show that dictionary learning can significantly improve the quality of NMR echo data with high noise level and effectively improve the accuracy and reliability of inversion results.

关键词： Dictionary learning Low-field NMR Denoising data processing T_(2)distribution

Methods of data processing for Trace Elements Analysis Using Laser Induced Breakdown Spectroscopy

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Plasma Science and Technology 2015年第11期17卷 944-947页

作者：王锐马晓红余琦宋阳赵华凤张敏廖延彪 Electronic Engineering Department Tsinghua University

With the development of Laser Induced Breakdown Spectroscopy （LIBS）, increasing numbers of researchers have begun to focus on problems of the application. We are not just satisfied with analyzing what kinds of elements are in the samples but are also eager to accomplish quantitative detection with LIBS. There are several means to improve the limit of detection and stability, which are important to quantitative detection, especially of trace elements, increasing the laser energy and the resolution of spectrometer, using dual pulse setup, vacuuming the ablation environment etc. All of these methods are about to update the hardware system, which is effective but expensive. So we establish the following spectrum data processing methods to improve the trace elements analysis in this paper： spectrum sifting, noise filtering, and peak fitting. There are small algorithms in these three method groups, which we will introduce in detail. Finally, we discuss how these methods affect the results of trace elements detection in an experiment to analyze the lead content in Chinese cabbage.

关键词： LIBS data processing limit of detection spectrum sift noise filtering peak fitting

The Implementation of Computer data processing Software for EAST NBI

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Plasma Science and Technology 2014年第10期16卷 984-987页

作者：张小丹胡纯栋盛鹏赵远哲吴德云崔庆龙 Institute of Plasma Physics Chinese Academy of Sciences

One of the most important project missions of neutral beam injectors is the implementation of 100 s neutral beam injection （NBI） with high power energy t.o the plasma of the EAST superconducting tokamak. Correspondingly, it＇s necessary to construct a high-speed and reliable computer data processing system for processing experimental data, such as data acquisition, data compression and storage, data decompression and query, as well as data analysis. The implementation of computer data processing application software （CDPS） for EAST NBI is presented in this paper in terms of its functional structure and system realization. The set of software is programmed in C language and runs on Linux operating system based on TCP network protocol and multi-threading technology. The hardware mainly includes industrial control computer （IPC）, data server, PXI DAQ cards and so on. Now this software has been applied to EAST NBI system, and experimental results show that the CDPS can serve EAST NBI very well.

关键词： NBI data processing LZO algorithm TCP

A program for SAXS data processing and analysis

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Chinese Physics C 2013年第10期37卷 110-115页

作者：李志宏 Beijing Synchrotron Radiation Facility Institute of High Energy PhysicsChinese Academy of Sciences

A computer program for small angle X-ray scattering （SAXS） data processing and analysis named *** written in Intel Visual Fortran has been developed. This paper briefly introduces its main theory and function.

关键词： SAXS data processing program

Cloud-Edge Collaborative Federated GAN Based data processing for IoT-Empowered Multi-Flow Integrated Energy Aggregation Dispatch

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Computers, Materials & Continua 2024年第7期80卷 973-994页

作者： Zhan Shi Electric Power Dispatching Control Center Guangdong Power Grid Co.Ltd.Guangzhou510030China

The convergence of Internet of Things(IoT),5G,and cloud collaboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data *** generative adversarial networks(GANs)are instrumental in resource scheduling,their application in this domain is impeded by challenges such as convergence speed,inferior optimality searching capability,and the inability to learn from failed decision making ***,a cloud-edge collaborative federated GAN-based communication and computing resource scheduling algorithm with long-term constraint violation sensitiveness is proposed to address these *** proposed algorithm facilitates real-time,energy-efficient data processing by optimizing transmission power control,data migration,and computing resource *** employs federated learning for global parameter aggregation to enhance GAN parameter updating and dynamically adjusts GAN learning rates and global aggregation weights based on energy consumption constraint *** results indicate that the proposed algorithm effectively reduces data processing latency,energy consumption,and convergence time.

关键词： IoT federated learning generative adversarial network data processing multi-flowintegration energy aggregation dispatch

data processing OF UNIVERSAL QUANTITATIVE METHOD IN STANDARDLESS X-RAY PHASE ANALYSIS

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Acta Metallurgica Sinica(English Letters) 1989年第11期2卷 348-353页

作者： LIN Shuzhi ZHANG Xizhang WANG Wenzhong, Institute of Metal Reaserch, Academia Sinica, Shenyang, China

Accuracy of coeffcient A_(isp) is related to the reference phase chosen during analysis. The cri- terion of choosing reference phase which may minimize the error of A_(isp) was deduced. The optimum results could be obtained by using the method of least squares if the number of sam- pies for analysis is more than the phase in samples. The procedure presented here is satisfacto- ryfor ordinary phase analysis.

关键词： X-ray diffraction analysis data processing

Application of Dynamic Linear Detecting Method in data processing of the Portable Blood Sugar Analyzer

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稀有金属材料与工程 2006年第A3期35卷 80-82页

作者： Xiaohao Wang Ran Liu Fei Tang Yangchun Yu Zhaoying Zhou State Key Laboratory of Precision Measurement Technology and Instruments Dept. of Precision Instruments Tsinghua Univ. Beijing 100084 China Dept. of Biomedical Engineering Tsinghua Univ. Beijing 100084 China

In this paper,a dynamic linear detecting method,that the non-linear coefficient NL% was led and the non-linearity of data were estimated continuously and dynamically and determined when NL% exceeded reference value (5%),was used for data processing and could solve the problem caused by the phenomenon of substrate depleting occurred following the redox reaction in portable blood sugar *** contrast to the conventional end-point method,the dynamic linear detecting method is based on multipoint data *** of measuring the calibration glucose solution with 8 various concentrations from 50 mg/dl to 400 mg/dl were carried out with the analyzer developed by our *** linear regression curve,whose correlation for the data was 0.9995 and the residual was 2.8080,were *** obtained correlation,residual, and the computation workload are all fit for the portable blood sugar analyzer.

关键词： data processing portable blood sugar analyzer dynamic linear detecting method