• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.183-183
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• 2020

Accurate quantitative precipitation estimation plays an important role in hydrological modelling and prediction. Instantaneous quantitative precipitation estimation (QPE) by utilizing the weather radar data is a great applicability for operational hydrology in a catchment. Previously, regression technique performed between reflectivity (Z) and rain intensity (R) is used commonly to obtain radar QPEs. A novel, recent approaching method which might be applied in hydrological area for QPE is Long Short-Term Memory (LSTM) Networks. LSTM networks is a development and evolution of Recurrent Neuron Networks (RNNs) method that overcomes the limited memory capacity of RNNs and allows learning of long-term input-output dependencies. The advantages of LSTM compare to RNN technique is proven by previous works. In this study, LSTM networks is used to estimate the quantitative precipitation from weather radar for an urban catchment in South Korea. Radar information and rain-gauge data are used to evaluate and verify the estimation. The estimation results figure out that LSTM approaching method shows the accuracy and outperformance compared to Z-R relationship method. This study gives us the high potential of LSTM and its applications in urban hydrology.

• 한국농공학회지
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• 제26권4호
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• pp.52-65
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• 1984

In general precise estimation of hourly of daily distribution of the long-term run-off should be very important in a design of source of irrigation. However, there have not been a satisfying method for forecasting of stationar'y long-term run-off in Korea. Solving this problem, this study introduces unit-hydrograph method frequently used in short-term run-off analysis into the long-term run-off analysis, of which model basin was selected to be Sumgin-river catchment area. In the estimation of effective rainfall, conventional method neglects the Soil moisture condition of catchment area, but in this study, the initial discharge (qb) occurred just before rising phase of the hydrograph was selected as the index of a basin soil moisture condition and then introduced as 3rd variable in the analysis of the reationship between cumulative rainfall and cumulative loss of rainfall, which built a new type of separation method of effective rainfall. In next step, in order to normalize significant potential error included in hydrological data, especially in vast catchment area, Snyder's correlation method was applied. A key to solution in this study is multiple correlation method or multiple regressional analysis, which is primarily based on the method of least squres and which is solved by the form of systems of linear equations. And for verification of the change of characteristics of unit hydrograph according to the variation of a various kind of hydrological charateristics (for example, precipitation, tree cover, soil condition, etc),seasonal unit hydrograph models of dry season(autumn, winter), semi-dry season (spring), rainy season (summer) were made respectively. The results obtained in this study were summarized as follows; 1.During the test period of 1966-1971, effective rainfall was estimated for the total 114 run-off hydrograph. From this estimation results, relative error of estimation to the ovservation value was 6%, -which is mush smaller than 12% of the error of conventional method. 2.During the test period, daily distribution of long-term run-off discharge was estimated by the unit hydrograph model. From this estimation results, relative error of estimation by the application of standard unit hydrograph model was 12%. When estimating by each seasonal unit bydrograph model, the relative error was 14% during dry season 10% during semi-dry season and 7% during rainy season, which is much smaller than 37% of conventional method. Summing up the analysis results obtained above, it is convinced that qb-index method of this study for the estimation of effective rainfall be preciser than any other method developed before. Because even recently no method has been developed for the estimation of daily distribution of long-term run-off dicharge, therefore estimation value by unit hydrograph model was only compared with that due to kaziyama method which estimates monthly run-off discharge. However this method due to this study turns out to have high accuracy. If specially mentioned from the results of this study, there is no need to use each seasonal unit hydrograph model separately except the case of semi-dry season. The author hopes to analyze the latter case in future sudies.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1630-1643
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• 2023

The correct situation awareness (SA) of operators is important for managing nuclear power plants (NPPs), particularly in accident-related situations. Among the three levels of SA suggested by Ensley, Level 3 SA (i.e., projection of the future status of the situation) is challenging because of the complexity of NPPs as well as the uncertainty of accidents. Hence, several prediction methods using artificial intelligence techniques have been proposed to assist operators in accident prediction. However, these methods only predict short-term plant status (e.g., the status after a few minutes) and do not provide information regarding the uncertainty associated with the prediction. This paper proposes an algorithm that can predict the multivariate and long-term behavior of plant parameters for 2 h with 120 steps and provide the uncertainty of the prediction. The algorithm applies bidirectional long short-term memory and an attention mechanism, which enable the algorithm to predict the precise long-term trends of the parameters with high prediction accuracy. A conditional variational autoencoder was used to provide uncertainty information about the network prediction. The algorithm was trained, optimized, and validated using a compact nuclear simulator for a Westinghouse 900 MWe NPP.

• 대한교통학회지
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• 제30권5호
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• pp.43-59
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• 2012

통행분포 예측시 목표년도가 단기일 경우에는 성장인자모형의 예측 정확도가 높고, 장기 목표년도의 경우에는 중력모형의 예측 정확도가 높은 것으로 인식되어 오고 있다. 이와 같은 예측모형 적용경향에 대한 검정을 위해 본 연구에서는 대구시 3개 년도(1988년, 1992년, 2004년)의 O-D표를 이용하여 통행분포 예측모형들의 정확도를 비교하였다. 비교는 분석 죤이 대죤인 경우와 중죤인 경우에서 예측모형별로 단기 목표년도의 정확도와 장기 목표년도 정확도를 구분하여 행하였다. 비교결과, 통행분포 예측모형의 통상적인 인식과 다른 결과가 있을 수 있다는 것이 규명되었다.

• 한국물환경학회지
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• 제22권6호
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• pp.1088-1093
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• 2006

In this study, the method of annual sediment estimation for reservoir long-term operation is proposed. Long-term daily precipitation and evaporation are predicted by Markov Chain. Using these values, reservoir inflow is simulated by NWS-PC model. Reservoir sediment load is estimated by sediment rating relation curve which is observed. From the simulation results, it was found that each simulated value by Markov Chain and NWS-PC was well compared to the observed ones and also estimated reservoir sediment was appropriate to the compared values using empirical equations. It is thought that the proposed method for estimation of reservoir sediment can be useful used to operate the reservoir.

• 전력전자학회논문지
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• 제26권3호
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• pp.183-191
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• 2021

A battery management system (BMS) provides some functions for ensuring safety and reliability that includes algorithms estimating battery states. Given the changes caused by various operating conditions, the state-of-health (SOH), which represents a figure of merit of the battery's ability to store and deliver energy, becomes challenging to estimate. Machine learning methods can be applied to perform accurate SOH estimation. In this study, we propose a Long-Term Recurrent Convolutional Network (LRCN) that combines the Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) to extract aging characteristics and learn temporal mechanisms. The dataset collected by the battery aging experiments of NASA PCoE is used to train models. The input dataset used part of the charging profile. The accuracy of the proposed model is compared with the CNN and LSTM models using the k-fold cross-validation technique. The proposed model achieves a low RMSE of 2.21%, which shows higher accuracy than others in SOH estimation.

• 한국수자원학회논문집
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• 제30권6호
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• pp.721-729
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• 1997

교량지점에서의 총세굴깊이는 세가지 성분 즉, 장기하상변동, 단면축소세굴, 그리고 국부세굴로 구성된다. 그러므로 장기하상변도의 분석은 교량지점에서의 총세굴깊이를 산정하는데 있어 중요하다고 할 수 있다. 본 연구에서는 CHARIMA모형과 HEC-6모형을 사용하여 남한강교 지점에서의 장기하상변동을 분석하였다. 분석결과, 5년 동안 정상류로 물이 흐를 경우 CHARIMA모형은 약 45cm의 하상고의 상승을 보여준 반면 HEC-6모형은 약 5cm정도 하상고가 저하되고 있음을 보여주었다. 5년 동안 부정류로 물이 흐를 경우 두 모형 모두 하상고가 심하게 변동됨을 보여주고 따라서 총세굴깊이 산정에 많은 영향을 미치고 있다. 그러므로 총세굴깊이를 적절하게 산정하기 위해서는 단면축소세굴과 국부세굴뿐만 아니라 장기하상변동 또한 정확히 산정해야 하겠다.

• 한국전자거래학회지
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• 제15권1호
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• pp.139-155
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• 2010

본 논문의 목적은 소프트웨어 사업대가기준의 중장기 발전 방향을 도출하고 소프트웨어 사업대가기준의 프레임워크를 제시하는 것이다. 본 논문에서는 첫째, 소프트웨어 생명주기상의 모든 단계와 현재의 소프트웨어 사업대가기준과 모형들이 검토되고 분석되어졌다. 둘째, 소프트웨어 사업대가기준의 중장기적 발전 대안으로 단가와 지침을 분리하여 운영하고, 시장자율기능을 확대하는 방안을 도출하였다. 그리고 소프트웨어 사업대가기준의 중장기 발전대안의 선결과제로 비용 리포지토리의 구축, 소프트웨어 사업대가 지침화, 다양한 사업대가기준 모형화 및 인증제 도입, 사업대가 전문가제도 도입이 제시되었다. 마지막으로 소프트웨어 사업대가기준의 중장기 발전대안의 단계별 이행계획이 제시되었다.

• Communications for Statistical Applications and Methods
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• 제24권4호
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• pp.325-337
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• 2017

In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.

• 한국건설관리학회논문집
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• 제8권6호
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• pp.207-215
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• 2007

본 연구는 학교건물의 유지관리를 위한 장기수선충당금 산정을 목적으로 수행되었으며, 이를 위해 서울 교육청에서 발주한 BTL 사업 대상 학교를 중심으로 사례를 선정하였다. 다음으로 사례 학교건물의 초기투자비용을 공종별로 분류한 후 장기 수선충당금을 산정하였다. 이렇게 산정된 공종별 장기수선충당금을 공동주택 장기수선충당금 산정방법과 연등가액 산정방법을 준용하여 비교 분석하였다. 위와 같은 목적과 방법에 따라 진행 된 본 연구의 결론을 요약하면 다음과 같다. 첫째: 사례 학교건물의 공종별 장기수선충당금의 비율을 정리하면 공사비용 대비 건축14.0%, 토목1.4%, 기계6.5%, 전기11.0%, 비품5.1%%, 기타1.0%의 분포를 나타냈다. 둘째: 산정된 공종별 장기수선충당금을 공동주택 장기수선충당금 산정방법과 연등가액 산정방법을 각각 이용하여 비용편차를 비교하였다.