• 한국환경과학회지
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• 제3권2호
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• pp.77-88
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• 1994

When we conduct environmental impact assessment, main contents consist of summary, project outline, environmental conditions, environmental impacts due to the project, mitigation devices, and alternative measures of harmful impact on environment. In this Paper, to understand how they really conduct air quality impact assessment and prediction and examine their effectiveness, we considered the provisions and actual case of environmental impact assessment in Korea with that in Japan. As a result, we propose a method of improving air quality impact assessment and Prediction, such as reflection of the result in environmental impact assessment, detailed assessment focused on relatively important environmental impact elements, field measurement investigation over four season and seven sucessive days, the uniformity of units, the proper model development to predict environmental concentration and a biennial environmental impact assessment for ex post management.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권4호
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1902-1912
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• 2024

This paper presents results from system-level modeling of a water-based reactor cavity cooling system using RELAP5-3D. The computational model is benchmarked with experimental data from a half-scale RCCS test facility at Argonne National Laboratory. The model prediction is first compared with a two-phase oscillatory baseline experimental case where mixed accuracy is obtained. The model shows reasonable prediction of mass flow rate, pressure, and temperature but significant overprediction of void fraction. The model prediction is then compared with a fault case where the inlet of the risers is gradually reduced using a throttling valve. As the valve is closed, the model is able to predict some major flow phenomena observed in the experiment such as the dampening of oscillations, the reintroduction of oscillations, as well as boiling, flashing, and geysering in the risers. However, the timeline of these events are not well captured by the model. The model is also used to investigate the evolution of flow regime in the chimney. This work highlights that the semi-empirical constitutive relations used in RELAP-3D could have a strong influence on the accuracy of the model in two-phase oscillatory flows.

• 스마트미디어저널
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• 제12권11호
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• pp.134-144
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• 2023

Nowadays, Deep Learning (DL) technology is being used in several government departments. South Korea imports a lot of seafood. If the demand for fishery products is not accurately predicted, then there will be a shortage of fishery products and the price of the fishery product may rise sharply. So, South Korea's Ministry of Ocean and Fisheries is attempting to accurately predict seafood imports using deep learning. This paper introduces the solution for the fish import prediction in South Korea using the Long Short-Term Memory (LSTM) method. It was found that there was a huge gap between the sum of consumption and export against the sum of production especially in the case of two species that are Hairtail and Pollock. An import prediction is suggested in this research to fill the gap with some advanced Deep Learning methods. This research focuses on import prediction using Machine Learning (ML) and Deep Learning methods to predict the import amount more precisely. For the prediction, two Deep Learning methods were chosen which are Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM). Moreover, the Machine Learning method was also selected for the comparison between the DL and ML. Root Mean Square Error (RMSE) was selected for the error measurement which shows the difference between the predicted and actual values. The results obtained were compared with the average RMSE scores and in terms of percentage. It was found that the LSTM has the lowest RMSE score which showed the prediction with higher accuracy. Meanwhile, ML's RMSE score was higher which shows lower accuracy in prediction. Moreover, Google Trend Search data was used as a new feature to find its impact on prediction outcomes. It was found that it had a positive impact on results as the RMSE values were lowered, increasing the accuracy of the prediction.

• 지능정보연구
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• 제25권3호
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• pp.239-251
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• 2019

본 논문은 학습데이터의 크기에 따른 사례기반추론기법이 주가예측력에 어떻게 영향을 미치는지 살펴본다. 삼성전자 주가를 대상을 학습데이터를 2000년부터 2017년까지 이용한 경우와 2015년부터 2017년까지 이용한 경우를 비교하였다. 테스트데이터는 두 경우 모두 2018년 1월 1일부터 2018년 8월 31일까지 이용하였다. 시계 열데이터의 경우 과거데이터가 얼마나 유용한지 살펴보는 측면과 유사사례개수의 중요성을 살펴보는 측면에서 연구를 진행하였다. 실험결과 학습데이터가 많은 경우가 그렇지 않은 경우보다 예측력이 높았다. MAPE을 기준으로 비교할 때, 학습데이터가 적은 경우, 유사사례 개수와 상관없이 k-NN이 랜덤워크모델에 비해 좋은 결과를 보여주지 못했다. 그러나 학습데이터가 많은 경우, 일반적으로 k-NN의 예측력이 랜덤워크모델에 비해 좋은 결과를 보여주었다. k-NN을 비롯한 다른 데이터마이닝 방법론들이 주가 예측력 제고를 위해 학습데이터의 크기를 증가시키는 것 이외에, 거시경제변수를 고려한 기간유사사례를 찾아 적용하는 것을 제안한다.

• 한국지리정보학회지
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• 제17권4호
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• pp.101-111
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• 2014

공간사건들은 데이터마이닝 분류알고리즘을 이용하여 예측 가능하며, 의사결정 트리는 대표적인 분류알고리즘들 중 하나로 사용되고 있다. 의사결정 트리는 레이블 값을 갖는 분류작업에 주로 사용되었으나 규칙평가 기법을 트리 리프노드 등급 계산에 응용하면서부터 공간사건 예측에 이용되고 있다. 이 논문에서는 의사결정 트리에서 사용되는 규칙평가 방법들을 공간예측에 적용하여 비교하였다. 실험을 위해 의사결정 트리 알고리즘인 C4.5알고리즘과 규칙 평가기법인 Laplace, M-estimate 및 m-branch 기법들을 구현하여 자연환경에서 발생되는 대표적인 공간예측 응용분야인 산사태에 적용하였다. 적용한 규칙 평가 기법들의 정확도 평가결과, 그 특성에 따라 정확도의 차이가 있었으며 m-branch가 가장 높은 성능을 보였다. 그러나 m-branch 및 M-estimate와 같이 별도의 파라미터를 갖는 경우 반복적으로 최적의 파라미터 값을 찾는 과정을 요구하였다. 따라서 적용 대상에 따라 선택적으로 활용할 수 있다. 이러한 의사결정 트리를 이용한 공간예측은 예측 결과뿐만 아니라 특정 위치에서의 예측결과에 대한 원인분석을 가능하게 함으로 다양한 응용을 가능하게 한다.

• 한국지반신소재학회논문집
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• 제10권4호
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• pp.61-70
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• 2011

본 연구에서는 TBM의 관입속도 예측에 대한 경험적 모델을 비교하기 위하여 현장사례를 이용하여 관입속도를 예측하였으며, 예측결과와 시공 시의 실측치를 비교 분석하여 합리적인 모델을 평가하였다. 관입속도 예측은 일축압축강도를 이용한 모델과 암석의 특성 및 TBM의 장비 특성을 고려한 모델로 적용하였다. 사례현장은 대부분 편마암으로 구성되어 있으며, 절리가 발달되어 약선대가 존재하기 때문에 암석의 일축압축강도가 불규칙적으로 나타났다. 일축압축강도를 이용한 예측결과에서 Graham(1976)의 모델은 낮은 강도의 경우, 비현실적인 예측결과가 나타나는 것으로 분석되었다. 평균 관입율을 이용한 각 모델들의 신뢰성을 분석한 결과, 암석의 특성 및 TBM 기계적 특성을 합리적으로 반영한 NTNU 모델(1998)이 가장 높은 것으로 확인되었다. 그러나 실측치와 비교한 결과에서는 일축압축강도를 바탕으로 예측하는 Tarkoy의 모델(1986)이 사례현장의 특성과 일치하는 것으로 분석되었다. 즉, TBM의 관입속도 예측 시에는 대상 암종, 지질특성 및 TBM의 장비 특성을 모두 고려하여 다양한 모델을 이용한 합리적인 예측이 수행되어야 한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.676-679
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• 1995

Practically, induction surface hardening is used widely to enhance the local strength of structure. In this study, Fatigue limit and its S-T characteristic for raw and induction hardened specimen of SCM440 is studied experimentally. The life prediction was considered by Juvinall's equation and its predicted result is compared with experiment.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2013년도 춘계 학술논문 발표대회
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• pp.65-66
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• 2013

As a result of executing Cone Calorimeter experiment on 12 samples among combustibles of domestic residential facilities, flooring materials showed higher HRR and THR than wall papers, and in case of toxicity and SPR, wall papers having adhesive components in one side by considering use conveniences were measured high.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1055-1060
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• 2001

Springing phenomena of ships is introduced with its concept, research history and approach methodology. Being a hydroelasticity problem, non-linear vibration and stochastic process, springing was formulated and modeled in vibration point of view separating hydrodynamic force into system properties and excitation force. Both RAO and response spectrum as well as wave spectrum were presented as a case study of springing analysis for a flexible vessel with wide breadth. The effect of advance speed, heading angle and loading condition were investigated as parametric study. The results and observations showed availability of analysis for the prediction of the ship springing behavior.