• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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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.

• Journal of Information Processing Systems
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• 제18권4호
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

• Computers and Concrete
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• 제25권6호
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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.

• 벤처창업연구
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• 제7권3호
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• pp.133-141
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• 2012

글로벌 경쟁 상황에 처한 현대의 모든 기업들은 고객의 니즈를 충족시키고, 이를 통한 경쟁력을 강화하기 위한 방안으로서 서비스를 이해하기 시작하면서 서비스에 대한 관심이 날로 증가하고 있다. 기업들이 제공하는 제품이나 서비스의 가치는 주로 고객과 서비스 제공자 간의 관계에서 형성되는 만족도의 정도로 정의되는 서비스 신뢰도에 의해 크게 좌우된다. 본 연구에서는, 유형의 제품이나 시스템의 실패 유형과 영향을 평가하는데 널리 사용되는 FMEA를 서비스의 신뢰도 평가에 적용하였다. 이를 위해, 서비스의 설계와 서비스 기능과 실패 간의 관계를 용이하게 표현할 수 있는 사건중심 프로세스 모델을 이용하였다. 본 연구의 목적은 서비스 프로세스 관점에서의 서비스 신뢰도를 평가하는 방법을 제시하는 것으로서, 이를 위해 fuzzy FMEA와 grey 이론을 이용하였다. 제안된 방법은 자동차정비 프로세스 사례에 적용하여 평가하였다.

• 한국수자원학회논문집
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• 제38권12호
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• pp.1061-1072
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• 2005

본 연구에서는 영산호의 상류에 위치한 나주유역의 홍수시 유출량을 실시간으로 예측하기 위하여 Grey홍수 유출모형을 개발하였다. 나주유역의 유출량은 나주수위관측소에서 실시간으로 측정하고 있으며, 이곳은 영산호의 유입홍수량을 예측과 홍수관리를 위한 주관측소이다. 모형의 지배방정식은 Grey시스템 이론에 근거하여 구성되었으며, 모형의 매개변수는 Grey 시스템매개변수의 조합으로 구성하였다. 모형의 차수는 실측자료와 모의결과를 비교하여 다른 차수 보다 양호한 결과를 나타내는 5차로 하였다. 모형의 보정시 예측결과와 실측치간의 RMSE는 $3.1\~290.5m^{3}/sec$를 나타냈으며, $R^{2}$는 $0.909\~0.999$를 나타냈다. 모형의 검정시 예측결과와 실측치간의 RMSE는 $20.6\~147.4m^{3}/sec$를 나타냈으며, $R^{2}는\;0.940\~0.998$를 나타냈다. 매개변수가 추정된 모형을 이용하여 담수호의 유입량을 하천수위 상태에 따라 예측한 결과, 하천수위가 상승할 경우와 하강할 경우의 예측 홍수량은 예측시간이 증가할수록 커지는 경향을 나타냈다. 또한, 하천수위가 첨두에 가까운 시기의 홍수량은 예측시간에 관계없이 실측자료와 비슷한 결과를 나타냈다. 이와 같은 결과는 Grey 홍수유출모형을 홍수시 담수호 유입량을 실시간으로 정확하게 예측하는데 적용할 수 있음을 나타낸다.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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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."

• 한국수자원학회논문집
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• 제42권1호
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• pp.61-73
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• 2009

본 연구에서는 다목적댐의 효율적인 홍수관리와 조기 홍수 경보시스템의 정확성을 향상시키기 위하여 두 가지 모형이 제안되었다. 두 모형은 상류 유입 홍수량과 하류 하천의 홍수량을 실시간으로 예측할 수 있는 능력을 각각 가지고 있다. 이들 모형은 남강댐 상류와 하류 홍수량의 실측치와 모의치를 비교하여 보정 및 검정되었으며, 실제 상황에서 모형의 홍수량 예측 능력이 평가되었다. 상류 유입량 예측 모형은 Grey 시스템 이론에 근거하였으며, 모형의 예측능력을 고려하여 6차 모형을 선정하였다. 서로 다른 자료 세트를 사용하여 보정된 모형들을 사용하여 예측한 홍수량과 실측자료를 비교하여 가장 적정한 모형이 선정되었으며, 검정 결과를 검토한 결과 선정된 모형이 양호한 예측결과를 제시하는 것으로 나타났다. 댐 하류 하천 홍수량 예측 모형은 Grey 모형과 수정 Muskingum 홍수 추적 모형을 병합하여 구성되었으며, 보정 및 검정을 통해서 모형의 예측 능력이 평가되었다. 제안된 모형들을 실시간 홍수량 예측에 적용한 결과, 비교적 양호한 예측결과를 나타냈다. 또한, 모형의 정확도를 향상시키기 위해서는 유출 단계를 고려한 모형의 보정 및 적용이 필요하다는 것이 밝혀졌다.

• 천문학회지
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• 제49권1호
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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.

• Computers and Concrete
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• 제26권2호
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• pp.175-183
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• 2020

Fly ash has become an important component of concrete as supplementary cementitious material with the development of concrete technology. To make use of fly ash efficiently, four types of fly ash with particle size distributions that are in conformity with four functions, namely, S.Tsivilis, Andersen, Normal and F distribution, respectively, were prepared. The four particle size distributions as functions of the strength and pore structure of concrete were thereafter constructed and investigated. The results showed that the compressive and flexural strength of concrete with the fly ash that conforming to S.Tsivilis, Normal, F distribution increased by 5-10 MPa and 1-2 MPa, respectively, compared to the reference sample at 28 d. The pore structure of the concrete was improved, in which the total porosity of concrete decreased by 2-5% at 28 d. With regarding to the fly ash with Andersen distribution, it was however not conducive to the strength development of concrete. Regression model based on the grey multiple linear regression theory was proved to be efficient to predict the strength of concrete, according to the characteristic parameters of particle size and pore structure of the fly ash.

• Journal of Information Processing Systems
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• 제8권4호
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.