• Journal of the Korean Data and Information Science Society
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• 제28권5호
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• pp.971-980
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• 2017

가변계수 회귀모형은 회귀계수의 동적변화를 모형화함으로써 종속변수와 입력변수의 관계에 대한 쉬운 해석이 가능하고 회귀계수의 변동성도 추정할 수 있는 장점을 지니고 있으므로, 여러 과학 분야에서 많은 주목을 받고 있다. 본 논문에서 입력변수와 출력변수의 오차를 효과적으로 고려한 가변계수 오차모형을 제안한다. 가변계수가 평활변수의 알려지지 않은 형태의 비선형함수이므로 이를 추정하기 위하여 커널 방법을 사용한다. 제안된 모형의 성능에 영향을 미치는 초모수의 최적값을 구하기 위하여 일반화 교차타당성 방법 또한 제안한다. 제안된 방법은 모의자료와 실제자료를 이용한 수치적 연구를 통하여 평가된다.

• 한국대기환경학회지
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• 제14권3호
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• pp.219-228
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• 1998

In the present investigation, a numerical model developed for the prediction of the wind flow over complex terrain is validated by comparing with the field experiments. For the solution of the Reynolds - Averaged Clavier- stokes equations which are the governing equations of the microscale atmospheric flow, the model is constructed based on the finite-volume formulation and the SIMPLEC pressure-correction algorithm for the hydrodynamic computation. The boundary- fitted coordinate system is employed for the detailed depiction of topography. The boundary conditions and the modified turbulence constants suitable for an atmospheric boundary- layer are applied together with the k- s turbulence model. The full- scale experiments of Cooper's Ridge, Kettles Hill and Askervein Hill are chosen as the validation cases . Comparisons of the mean flow field between the field measurements and the predicted results show good agreement. In the simulation of the wind flow over Askervein Hill , the numerical model predicts the three dimensional flow separation in the downslope of the hill including the blockage effect due to neighboring hills . Such a flow behavior has not been simulated by the theoretical predictions. Therefore, the present model may offer the most accurate prediction of flow behavior in the leeside of the hill among the existing theoretical and numerical predictions.

• 기술혁신학회지
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• 제9권2호
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• pp.304-324
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• 2006

재무분석가들은 기업의 파산에 양향을 미치는 예측변수를 탐색하기 위해서 상당한 연구가 수행되어 왔다. 그러나 기술지향적 중소벤처기업은 일반적으로 역사적 재무자료가 부족하고, 기술경쟁력 수준에 따라 잠재적인 고성장과 고위험이 존재한다. 본 논문에서는 재무자료 대신에 기술력평가 자료를 이용하여 파산을 예측하기 위해서 파산예측 판별모형을 제안하였고, 모형의 정분류율을 통해서 예측력을 검증하기 위해서 교차타당성방법, 최대사후확률방법 등을 사용하였다. 분석결과 중소 벤처기업의 파산예측모형으로 선형판별모형이 로지스틱판별모형보다 적합한 모형이고, 표본자료에 대한 정분류율 추정은 약 69% 이고 정분류율 예측은 약 67% 가 될 것으로 기대된다.

• 한국환경농학회지
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• 제33권1호
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• pp.37-43
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• 2014

BACKGROUND: Water quality data are collected less frequently than flow data because of the cost to collect and analyze, while water quality data corresponding to flow data are required to compute pollutant loads or to calibrate other hydrology models. Regression models are applicable to interpolate water quality data corresponding to flow data. METHODS AND RESULTS: A regression model was suggested which is capable to consider flow and time variance, and the regression model coefficients were calibrated using various measured water quality data with genetic-algorithm. Both LOADEST and the regression using genetic-algorithm were evaluated by 19 water quality data sets through calibration and validation. The regression model using genetic-algorithm displayed the similar model behaviors to LOADEST. The load estimates by both LOADEST and the regression model using genetic-algorithm indicated that use of a large proportion of water quality data does not necessarily lead to the load estimates with smaller error to measured load. CONCLUSION: Regression models need to be calibrated and validated before they are used to interpolate pollutant loads, as separating water quality data into two data sets for calibration and validation.

• Geomechanics and Engineering
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• 제18권5호
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• pp.493-502
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• 2019

Internal stability is an important safety issue for levees, embankments, and other earthen structures. Since a large part of the world's population lives near oceans, lakes and rivers, floods resulting from breaching of dams can lead to devastating disasters with tremendous loss of life and property, especially in densely populated areas. There are some main factors that affect the internal stability of dams, levees and other earthen structures, such as the erodibility of the soil, the water velocity inside the soil mass and the geometry of the earthen structure, etc. Thus, the mechanism of internal erosion and stability of soils is very complicated and it is vital to investigate the assessment methods of internal stability of soils in embankment dams and their foundations. This paper presents an improved support vector machine (SVM) model to predict the internal stability of soils. The grid search algorithm (GSA) is employed to find the optimal parameters of SVM firstly, and then the cross - validation (CV) method is employed to estimate the classification accuracy of the GSA-SVM model. Two examples of internal stability of soils are presented to validate the predictive capability of the proposed GSA-SVM model. In addition to verify the effectiveness of the proposed GSA-SVM model, the predictions from the proposed GSA-SVM model were compared with those from the traditional back propagation neural network (BPNN) model. The results showed that the proposed GSA-SVM model is a feasible and efficient tool for assessing the internal stability of soils with high accuracy.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.197-206
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• 2019

The purpose of this study is to develop and validate a model for diagnosing core competencies at the higher education level. Based on literature reviews, a potential model for core competencies at university was suggested. A tool for validating the model was composed of 24 items, which were delivered to 226 professors and administrative staffs, 730 students, and 134 graduates & external industrial experts. Five constructs (core competencies) were extracted from the data collected among professors and administrative staff responding to the importance of the items. The results of importance and performance surveys on core competencies with students were respectively 3.28 to 3.66 and 2.68 to 3.28 (4-point Likert scale). Statistical differences between importance level and performance level were found in all the sub-categories of core competencies. Borich priority determination formula and Locus for Focus Model were used for the determination of the priority of needs. Importance survey among graduates and external experts showed that the mean of each items ranged from 2.80 to 3.76 (4-point Likert scale). The overall results of the analyses suggest that the final model is appropriate for measuring the core competencies.

• 한국항공운항학회지
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• 제29권4호
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• pp.37-44
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• 2021

In case of South Korea, the airspace which airlines can operate is extremely limited due to the military operational area located within the Incheon flight information region. As a result, safety problems such as mid-air collision between aircraft or Traffic alert and Collision Avoidance System Resolution Advisory (TCAS RA) may occur with higher probability than in wider airspace. In order to prevent such safety problems, an mid-air collision risk detection model based on Detect-And-Avoid (DAA) well clear metrics is investigated. The model calculates the risk of mid-air collision between aircraft using aircraft trajectory data. In this paper, the practical use of DAA well clear metrics based model has been validated. Aviation safety data such as aviation safety mandatory report and Automatic Dependent Surveillance Broadcast is used to measure the performance of the model. The attributes of individual aircraft track data is analyzed to correct the threshold of each parameter of the model.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.117-117
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• 2020

The main objective of this study was to setup model and evaluate the model performance for streamflow simulation in Burundi using Soil and Water Assessment Tool (SWAT) model. The total area of Burundi is 27,834 ㎢. The elevation of Burundi ranges from 780 m to 2,700m. The West and East are low lands, while the Central part is high land. The topographic data (30 meters Digital Elevation Model) and land use and land cover data of Burundi were obtained respectively from Shuttle Radar Topography Mission (SRTM) and the Regional Centre for Mapping of Resources for Development (RCMRD). The soil data used was obtained from Food and Agriculture Organization (FAO). The local weather data and discharge data were provided by Burundi Hydro meteorological Service (IGEBU). Mean Areal Precipitation (MAP) and Mean Areal Temperature (MAT) were estimated. The streamflow simulation was done for the period 1980-2017. The calibration and validation of river discharge was performed at a daily time step from 2005 through 2011 as the calibration period and 2012 up to 2017 as the validation period. The findings show that streamflow decreases during Jun to September and increases during March to May and October to December.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 2008년도 추계학술논문발표회 논문집
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• pp.438-443
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• 2008

Fire model shall be verified and validated to reliably show the predictive capabilities for a specific use. In the process of model verification and validation, both the acceptable uses and limitation of fire model are established. In this study, the results of FDS simulation are compared with the data of PRISME experiment such as temperature, heat release rate, heat flux, product concentrations in the under-ventilated two-room condition. Furthermore, the sensitivity of FDS under ventilation condition changes are evaluated. FDS provide the reliable prediction for under-ventilated two-room fire scenario with slightly deviation.

• 지식경영연구
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• 제1권1호
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• pp.91-107
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• 2000

This paper proposes the Organizational Knowledge Discovery Process Model (OK-DPM) as an initiative for developing a knowledge management methodology. OK-DPM is a model designed to effectively discover knowledge useful to the organization. It explains the knowledge discovery process from the conceptual level to the application level. It decomposes the organizational knowledge discovery process into 3 sub-processes; Creation, Suggestion and Validation. For each sub-process, design components are identified and possible methods for supporting each one are suggested. Also, the relationship patterns between the knowledge discovery process and knowledge type are explored. By applying OK-DPM to two real cases where the knowledge management projects are ongoing, the model was validated and revised. Even though we need to investigate with more cases to refine the OK-DPM, we found that it could provide some insights in developing the effective knowledge discovery process.