• Proceedings of the Korean Nuclear Society Conference
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• 1997.05b
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• pp.92-97
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• 1997

경수로용 전산코드인 ERAPCON2를 CANDU 핵연료의 거동에 사용하기 위하여 소결체-피복관틈새 열전도 모형과 소결체내 중성자속 분포 모형을 개조하였다. 기존의 CANDU핵연료 전산코드와 비교한 결과 CANDU핵연료의 열적거동 분석에 있어 거의 동일한 결과를 얻었다. 이를 사용하여 DUPIC 핵연료의 열적 거동특성을 알아보았다. 고용성 핵분열생성물에 의해 감소된 DUPIC 핵연료의 열전도도에 의하여 핵연료 중심부 온도가 증가됨을 알 수 있었다. 선출력 500W/cm에서 중심온도가 230-320K 정도 증가하였다. 따라서, DUPIC핵연료 설계에서 중심온도 증가에 대한 세밀한 분석이 요구된다.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.281-289
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• 2019

In this study, the typhoon damage forecasting model was developed for southern inland district. The typhoon damage in the inland district is caused by heavy rain and strong winds, variables are many and varied, but the damage data of the inland district are not enough to develop the model. The hydrological data related to the typhoon damage were hour maximum rainfall amount which is accumulated 3 hour interval, the total rainfall amount, the 1-5 day anticipated rainfall amount, the maximum wind speed and the typhoon center pressure at latitude 33° near the Jeju island. The Multivariate Analysis such as cluster Analysis considering the lack of damage data and principal component analysis removing multi-collinearity of rainfall data are adopted for the damage forecasting model. As a result of applying the developed model, typhoon damage estimated and observed values were up to 2.2 times. this is caused it is difficult to estimate the damage caused by strong winds and it is assumed that the local rainfall characteristics are not considered properly measured by 69 ASOS.

• Information Systems Review
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• v.26 no.2
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• pp.169-183
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• 2024

This study summarizes improvement strategies for addressing the imbalance problem in observed default data that must be considered when constructing a default model and compares and analyzes the performance improvement effects using data resampling techniques and default threshold adjustments. Empirical analysis results indicate that as the level of imbalance resolution in the data increases, and as the default threshold of the model decreases, the recall of the model improves. Conversely, it was found that as the level of imbalance resolution in the data decreases, and as the default threshold of the model increases, the precision of the model improves. Additionally, focusing solely on either recall or precision when addressing the imbalance problem results in a phenomenon where the other performance evaluation metrics decrease significantly due to the trade-off relationship. This study differs from most previous research by focusing on the relationship between improvement strategies for the imbalance problem of default data and the enhancement of default model performance. Moreover, it is confirmed that to enhance the practical usability of the default model, different improvement strategies for the imbalance problem should be applied depending on the main purpose of the model, and there is a need to utilize the F_β Score as a performance evaluation metric.

• Journal of the Korean Geographical Society
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• v.50 no.3
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• pp.277-287
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• 2015

This paper addresses limitations of land-change modeling application in the context of REDD (Reducing Emissions from Deforestation and forest Degradation). REDD is an international conservation policy that aims to protect forests via carbon credit generation and trading. In REDD, carbon credits are generated only if there is measurable quantied carbon sequestration activities that are additional to business-as-usual (BAU). A "reference level" is defined as simulated baseline carbon emissions for the future under a BAU scenario, and predictive land-change modeling plays an important role in constructing reference levels. It is tested in this research how predictive accuracies of two land-change models, namely Geographic Emission Benchmark (GEB) and GEOMOD, vary with respect to different spatial scales: Xishuangbanna prefecture and Yunnan province. The accuracies are measured by Figure of Merit. In this Chinese case study, it turns out that GEB's better performance is mainly due to quantity (e.g., how many hectares of forest will be converted to agricultural land?) rather than spatial allocation (e.g., where will the conversion happen?). As both quantity and allocation are crucial in REDD reference level setting it appears to be fundamental to systematically analyze accuracies of quantity and allocation independently in pursuit of accurate reference levels.

• International Commerce and Information Review
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• v.16 no.3
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• pp.73-96
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• 2014

The purpose of this research is to evaluate a short-term export demand forecasting model reflecting individual passenger vehicle brands and market characteristics by using Vector Autoregressive (VAR) models that are based on multivariate time-series model. The short-term export demand forecasting model was created by discerning theoretical potential factors that affect the short-term export demand of individual passenger vehicle brands. Quarterly short-term export demand forecasting model for two Korean small vehicle brands (Accent and Avante) were created by using VAR model. Predictive value at t+1 quarter calculated with the forecasting models for each passenger vehicle brand and the actual amount of sales were compared and evaluated by altering subject period by one quarter. As a result, RMSE % of Accent and Avante was 4.3% and 20.0% respectively. They amount to 3.9 days for Accent and 18.4 days for Avante when calculated per daily sales amount. This shows that the short-term export demand forecasting model of this research is highly usable in terms of prediction and consistency.

• Journal of Global Scholars of Marketing Science
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• v.16 no.4
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• pp.39-54
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• 2006

Marketing managers hope to maximize the success rate of new products by satisfying various needs of consumers. For this, an analysis called 'conjoint analysis' has been frequently applied in the process of new product development. This study was performed to compare the predictability of diverse conjoint analyses in choice of general hospitals. The comparison was performed among four models of traditional conjoint analysis and choice-based conjoint analysis. Results show that the hybrid conjoint analysis, which combined the traditional conjoint analysis and the choice-based conjoint model showed the highest predictive accuracy. Still two models show similar estimates of utility.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1652-1660
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• 2009

The main objective of this research is to build a behavior prediction model of gameplay for MMO (Massively Multiplayer Online) game using the GOMS analysis method. GOMS analysis is an observational approach to HCI(Human Computer Interaction) to model and predict behaviors of a human operator in a highly interactive task. In this research, a pilot experiment was previously conducted with three skilled gamers. The gamers were provided with the goals and operators through the user's guide book, and they found methods and selection rules while being observed. Based on the results obtained from the pilot study, this research was expanded and the model was further tested with 30 subjects (game experts). The new outcomes revealed that the relevance of GOMS analysis for predicting selection rules is 96.25% according to the degree of abstraction and 77.35% based on the degree of complexity. This research will provide game designers with a new testing mechanism in the early development stages, in order to improve the quality of the game product.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.131-139
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• 2002

This study introduces a developed artificial neural networks(ANN) model as a more efficient and reliable prediction model in operating speed Prediction with the 85th percentile horizontal curve of two-way rural highway in the aspect of evaluating highway design consistency. On the assumption that the speed is decided by highway geometry features, total 30 survey sites were selected. Data include currie radius, curve length, intersection angle, sight distance, lane width, and lane of those sites and were used as input layer data of the ANN. The optimized model structure was drawn by number of unit of hidden layer, learning coefficient, momentum coefficient, and change in learning frequency in multi-layer a ANN model. To verify learning Performance of ANN, 30 survey sites were selected while data in obtained from the 20 cites were used as learning data and those from the remaining 10 sites were used as predictive data. As a result of statistical verification, the model D of 4 types of ANN was evaluated as the most similar model to the actual operating speed value: R2 was 85% and %RMSE was 0.0204.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.207-215
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• 2009

Generally, traffic accidents can be influenced by variables driving conditions including geometric, roadside design, and traffic conditions. Under the circumstance, homogeneous roadway segments were firstly identified using typical geometric variables obtained from field data collections in this study. These field data collections were conducted at highways located in several areas having various regional conditions for examples, outside metropolitan city; level and rolling rural areas. Due to many zero cells in crash database, a Zero Inflated Poisson model was used to develop crash prediction model to overestimated results in this study. It was found that EXPO, radius, grade, guardrail, mountainous terrain, crosswalk and bus-stop have statistically significant influence on vehicle to vehicle crashes at rural multi-lane roadway segments.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.353-366
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• 2018

This study uses mixed-effects models to predict thigh soft tissue artefact (STA), relative movement of soft tissue such as skin to femur occurring during hip joint motions. The random effects in the model were defined as STA and the fixed effects in the model were considered as skeletal motion. Five male subjects without musculoskeletal disease were selected to perform various hip joint rotational motions. Linear mixed-effects models were applied to markers' position vectors acquired from non-invasive method, photogrammetry. Predicted random effects showed similar patterns of STA among subjects. Large magnitudes of STA appeared on the points near the hip joint regardless of sides; however, small values appeared on the distal anterior.