• Title/Summary/Keyword: Grey Theory

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Analysis of Flatness of a Two-Axis Linear Motor with Grey Theory (그레이 이론을 이용한 2 축 리니어 모터의 평면도 분석)

  • 오준모;김준현;최우천
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.10a
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    • pp.686-689
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    • 2004
  • As the demands of X-Y linear motors increase, it becomes very important to measure flatness errors and to compensate them. In this study, in order to investigate flatness errors, a laser interferometer is used for measurement. To improve the measurement efficiency, a Union Jack method is adopted instead of a square method. The square method is frequently used because of its accuracy, but it requires many measurement points. In this study, the Union Jack method with Grey Theory is used. By using the Grey Theory, unmeasured data are predicted, and these are compared with results of the square method. The results show that the Union Jack method with Grey Theory is accurate enough to replace the square method.

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Evaluation of Vehicle and Pedestrian Environments using Grey System Theory (Grey System Theory를 이용한 차량 및 보행환경 통합평가)

  • Lee, Jin-Gak;Son, Yeong-Tae;Han, Sang-Jin;Park, Jin-Yeong;Lee, Sang-Hwa
    • Journal of Korean Society of Transportation
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    • v.28 no.4
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    • pp.141-156
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    • 2010
  • In this paper, understanding there is a limitation with a comprehensive and network approach for the evaluation of existing vehicle and pedestrian environments, the authors focus on developing an integrated approach to assessing these environments. The network evaluation here means the assessment at a three-dimensional level that includes evaluation methods of lines/axes in a spatial concept as well as integration of evaluation indicators being used for vehicles and the walking environment. Grey System Theory (GST) was applied based on the theoretical background for network and comprehensive integrated evaluation, and the evaluation of the vehicle and pedestrian environment was performed by assigning target areas to walking preference zones. As a result of the comprehensive evaluation and analysis by GST, even if the service level is the same as the operating indicators (Highway Capacity Manual) of the vehicle and pedestrian environment, or relatively better, it was identified that the total score could be varied over Grey Category because the observed data are calculated after considering the weights between evaluation indicators by the range of Grey Category on the comprehensive evaluation. Considering comprehensively these points, although the indicators on the operation of roads are relatively good, in the event that the indicators on the safety of roads are bad, it was known that the scores over Grey Category also could be changed. The result is that this evaluation method can be used to evaluate the network concept per lane (per axis) as well as to diagnose the current state by type of urban street in the future.

Evaluating Service Reliability focused on Failure Modes (실패모드에 근거한 서비스 신뢰도 평가모델)

  • Oh, Hyung-Sool
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.7 no.3
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    • pp.133-141
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    • 2012
  • Service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs and survive in today's competitive market environment. The value of services depends mainly on service reliability that is identified by satisfaction derived from the relationship between customer and service provider. In this paper, we extend concepts from the failure modes and effects analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using fuzzy failure mode effects analysis (FMEA) and grey theory. We define the failure mode of service as interaction ways that can be failed in a service delivery process. The fuzzy set theory is used to characterize service reliability based on linguistic terms during FMEA. Grey theory is employed to determine the degree of relation and ranking among risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.

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A Modified Grey-Based k-NN Approach for Treatment of Missing Value

  • Chun, Young-M.;Lee, Joon-W.;Chung, Sung-S.
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.2
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    • pp.421-436
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    • 2006
  • Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the deng's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(Wen's GRG & weighted mean) method is the best of any other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

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A Study on the Treatment of Missing Value using Grey Relational Grade and k-NN Approach

  • Chun, Young-Min;Chung, Sung-Suk
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.55-62
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    • 2006
  • Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

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An optimal classification method for risk assessment of water inrush in karst tunnels based on grey system theory

  • Zhou, Z.Q.;Li, S.C.;Li, L.P.;Shi, S.S.;Xu, Z.H.
    • Geomechanics and Engineering
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    • v.8 no.5
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    • pp.631-647
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    • 2015
  • Engineers may encounter unpredictable cavities, sinkholes and karst conduits while tunneling in karst area, and water inrush disaster frequently occurs and endanger the construction safety, resulting in huge casualties and economic loss. Therefore, an optimal classification method based on grey system theory (GST) is established and applied to accurately predict the occurrence probability of water inrush. Considering the weights of evaluation indices, an improved formula is applied to calculate the grey relational grade. Two evaluation indices systems are proposed for risk assessment of water inrush in design stage and construction stage, respectively, and the evaluation indices are quantitatively graded according to four risk grades. To verify the accuracy and feasibility of optimal classification method, comparisons of the evaluation results derived from the aforementioned method and attribute synthetic evaluation system are made. Furthermore, evaluation of engineering practice is carried through with the Xiakou Tunnel as a case study, and the evaluation result is generally in good agreement with the field-observed result. This risk assessment methodology provides a powerful tool with which engineers can systematically evaluate the risk of water inrush in karst tunnels.

A Prediction Model Based on Relevance Vector Machine and Granularity Analysis

  • Cho, Young Im
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.3
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    • pp.157-162
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    • 2016
  • In this paper, a yield prediction model based on relevance vector machine (RVM) and a granular computing model (quotient space theory) is presented. With a granular computing model, massive and complex meteorological data can be analyzed at different layers of different grain sizes, and new meteorological feature data sets can be formed in this way. In order to forecast the crop yield, a grey model is introduced to label the training sample data sets, which also can be used for computing the tendency yield. An RVM algorithm is introduced as the classification model for meteorological data mining. Experiments on data sets from the real world using this model show an advantage in terms of yield prediction compared with other models.

Dynamic fracture catastrophe model of concrete beam under static load

  • Chen, Zhonggou;Fu, Chuanqing;Ling, Yifeng;Jin, Xianyu
    • Computers and Concrete
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    • v.25 no.6
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    • pp.517-523
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    • 2020
  • An experimental system on three point bending notched beams was established to study the fracture process of concrete. In this system, the acoustic emission (AE) was used to build the cumulative generation order (AGO) and dynamically track the process of microcrack evolution in concrete. A grey-cusp catastrophe model was built based on AE parameters. The results show that the concrete beams have significant catastrophe characteristic. The developed grey-cusp catastrophe model, based on AGO, can well describe the catastrophe characteristic of concrete fracture process. This study also provides a theoretical and technical support for the application of AE in concrete fracture prediction.

NON-GREY RADIATIVE TRANSFER IN THE PHOTOSPHERIC CONVECTION : VALIDITY OF THE EDDINGTON APPROXIMATION

  • BACH, KIEHUNN
    • Journal of The Korean Astronomical Society
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    • v.49 no.1
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    • pp.1-8
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    • 2016
  • The aim of this study is to describe the physical processes taking place in the solar photosphere. Based on 3D hydrodynamic simulations including a detailed radiation transfer scheme, we investigate thermodynamic structures and radiation fields in solar surface convection. As a starting model, the initial stratification in the outer envelope calculated using the solar calibrations in the context of the standard stellar theory. When the numerical fluid becomes thermally relaxed, the thermodynamic structure of the steady-state turbulent flow was explicitly collected. Particularly, a non-grey radiative transfer incorporating the opacity distribution function was considered in our calculations. In addition, we evaluate the classical approximations that are usually adopted in the onedimensional stellar structure models. We numerically reconfirm that radiation fields are well represented by the asymptotic characteristics of the Eddington approximation (the diffusion limit and the streaming limit). However, this classical approximation underestimates radiation energy in the shallow layers near the surface, which implies that a reliable treatment of the non-grey line opacities is crucial for the accurate description of the photospheric convection phenomenon.

Assessing the Unemployment Problem Using A Grey MCDM Model under COVID-19 Impacts: A Case Analysis from Vietnam

  • NGUYEN, Phi-Hung;TSAI, Jung-Fa;NGUYEN, Hong-Phuc;NGUYEN, Viet-Trang;DAO, Trong-Khoi
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.12
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    • pp.53-62
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    • 2020
  • The COVID 19 pandemic has led to a new global recession and is still causing a lot of issues because of the delays in the employment of people. This scenario has severe consequences for many countries' labor markets in the world. This problem's complexity and importance requires an integrated method of subjective and objective evaluation rather than intuitive decisions. This research aims to investigate sustainable indexes for assessing the unemployment problem by using a Multi-Criteria Decision-Making Model (MCDM). Grey theory and Decision Making Trial and Evaluation Laboratory (GDEMATEL) are deployed to transform the experts' opinions into quantitative data. The analysis based on 20 crucial criteria is employed to determine the weights of sustainability of unemployment problems. The results revealed that the top ten of determinants are Economic growth, Industrialization, Foreign direct investment, Real GDP per capita, Education level, Trade Openness, Capacity Utilization Rate, Urbanization, Employability skills, Education system expansion, which have the most significant effects on the unemployment rate under COVID 19 impacts. Furthermore, GDEMATEL could effectively assess the sustainable indicators for unemployment problems in "deep and wide" aspects. The study proposes the Grey MCDM model, contributes to the literature, provides future research directions, and helps policymakers and researchers achieve the best solutions to the unemployment problems under "economic shocks."