• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.548-551
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• 2003

부산 금정산 지역의 지하수위와 강우량과의 관계를 알아보고자 시계열 분석을 통하여 자기상관함수와 상호상관함수를 구하였다. 이를 위하여 금정산 산성마을 주변의 19개 관측공 중 자동수위측정기가 설치된 4개 관측공(KJ2, KJ8, KJ15, KJ19)의 지하수위 자료와 부산지역의 강우량 자료를 이용하였다. 지하수위 및 강수량은 각각 1일 평균, 1일 누적 값을 이용하였다. 자기상관분석의 경우, KJ2와 KJ19의 경우 지연시간이 2일 이내, KJ8의 경우는 3일 이내에 0으로 수렴하며, KJ15의 경우는 지연시간이 8일째에 0으로 수렴한다. 강수량과 지하수위의 교차상관분석결과, KJ2, KJ15, KJ19호 공은 지연시간이 0일 때 교차상관함수가 각각 0.6572, 0.6303, 0.7857이교 KJ8호 공은 지연시간이 1일 때 0.7141이다. 또한 대부분 짧은 지연시간에 교차상관함수가 0으로 수렴한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.207-207
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• 2023

데이터 기반 강수 예측 모델은 극한 강수 이벤트의 크기를 과소 추정하는 경향이 있다. 이는 훈련 데이터에 극한 강수 이벤트보다 일반적인 강수 이벤트가 많이 포함되어 있기 때문이다. 본 연구는 이러한 딥러닝의 데이터 불균형 문제를 해소하고자 모델을 학습시킬 때 격자별 극한 강수에 더 큰 가중치를 주어 극한 강수 예측의 정확성을 높이는 방법을 제안한다. 딥러닝 모델 중 공간-시간 필드를 정확하게 예측할 수 있는 ConvLSTM 기반 강수 예측 모델을 활용하여 레이더 강수량을 예측하였다. 먼저, 훈련 기간 동안의 강수 이벤트의 누적 분포 함수 CDF(Cummulative distribution funcion)을 그린 후 극한 강수 이벤트와 일반적인 강수 이벤트의 분포를 확인하였다. 그다음, 적은 분포를 가진 극한 강수 이벤트의 더 큰 가중치를 두어 모델을 학습시켰다. 이 모델은 대한민국 중부 지역 (200km x 200km)의 5km-10분 해상도 레이더-계량기 복합 강수 필드에 대해 2009-2014년 기간 동안 훈련 되었고 2015-2016년 동안 모델의 훈련을 검증 하였고, 2017-2018년 동안 테스트 되었다. 다양한 가중치 함수를 기반으로 훈련 시킨 결과 최적화 가중치 함수 모델의 평균 NSE는 0.6 평균 RMSE는 0.00015 그리고 극한 강수 이벤트만 따로 추출한 평균 MAE는 6이다. 결과적으로 제안된 모델은 기존 방법에 비해 예측 성능을 향상 시켰으며, 격자별 가중치를 두었을 경우 일반적인 강수 이벤트 뿐만 아니라 극한 강수 이벤트의 예측의 정확도를 향상시켰다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.5A
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• pp.836-845
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• 2001

본 논문에서는 시간 선택성 다중경로 이동 무선 채널을 다양한 방법으로 모델링 하고 그에 따른 여러 가지 특성평가를 제시하였다. 모델링 방법에는 Jakes 방식과 시간 영역에서 독립적인 두 개의 가우시안 잡음 발생기와 정형필터(shaping filter)를 사용하는 방식 및 주파수 영역에서 필터링 하는 방식이 있다. 이 세 가지 모델링 방법의 성능을 진폭의 자기상관함수, 상호상관함수, 누적분포함수(Cumulative Distribution Function), 레벨 교차율(Level Crossing Rate), 평균 페이딩 지속 시간(Average Duration of Fades), 위상차의 확률 밀도, 위상차의 자기상관함수 등의 측면에서 시뮬레이션하고 그 결과치와 이론치 간의 특성 비교를 제시하였다. 특히, 확산 대역 시스템을 고려했을 때 이상적인 채널 추정을 가정한 레이크 수신기에서의 BER 성능을 다중경로 개수에 따라 보임으로써 여러 가지 채널 모델링 중에서 주파수 영역에서 필터링 하는 방식이 이동 무선 채널을 모델링 하는데 있어 가장 적합하다는 것을 보였다. 마지막으로 비대칭 도플러(Doppler) 스펙트럼을 모델링 하는 것도 주파수 영역에서 필터링 하는 방식이 편리하다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1186-1192
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• 2008

The reliability of gas turbine engine blades was studied. Yield strength, Young’s modulus, engine speed and gas temperature were considered as statistically independent random variables. The failure probability was calculated using five different methods. Advanced Mean Value Method was the most efficient without significant loss in accuracy. When random variables were assumed to have normal, lognormal and Weibull distributions with the same means and standard deviations, the CDF of limit state equation did not change significantly with the distribution functions of random variables. The normalized sensitivity of failure probability with respect to standard deviations of random variables was the largest with gas temperature. The effect of means and standard deviations of random variables was studied. The increase in the mean of gas temperature and the standard deviation of engine speed increased the failure probability the most significantly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1756-1761
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• 2021

Although the COVID-19 outbreak that occurred in Wuhan, Hubei around December 2019, seemed to be gradually decreasing, it was gradually increasing as of November 2020 and June 2021, and estimated confirmed cases were 192 million worldwide and approximately 184 thousand in South Korea. The Central Disaster and Safety Countermeasures Headquarters have been taking strong countermeasures by implementing level 4 social distancing. However, as the highly infectious COVID-19 variants, such as Delta mutation, have been on the rise, the number of daily confirmed cases in Korea has increased to 1,800. Therefore, the number of cumulative confirmed COVID-19 cases is predicted using ARIMA algorithms to emphasize the severity of COVID-19. In the process, differences are used to remove trends and seasonality, and p, d, and q values are determined and forecasted in ARIMA using MA, AR, autocorrelation functions, and partial autocorrelation functions. Finally, forecast and actual values are compared to evaluate how well it was forecasted.

• Journal of the Korean Geotechnical Society
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• v.28 no.11
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• pp.5-16
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• 2012

Since geologic data are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction. In this paper, the assessment of the local uncertainty of prediction for the depth to weathered soil was performed by using the indicator kriging. A conditional cumulative distribution function (ccdf) was first modeled, and then E-type estimate was computed for the spatial distribution of the depth to the weathered soil. Also, optimal estimate of spatial distribution for the depth to weathered soil was determined by using ccdf and loss function. The design procedure and method considering the minimum expected loss presented in this paper can be used in the decision-making process for geotechnical engineering design.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.453-461
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• 2013

This paper describes evaluation procedures and experimental results for the estimation of Cumulative Distribution Functions (CDF) giving best-fit to the sample data in the Probability based risk Evaluation Techniques (PET) which is to assess the risks of a small-sized sea floater. The CDF in the PET is to provide the reference values of risk acceptance criteria which are to evaluate the risk level of the floater and, it can be estimated from sample data sets of motion response functions such as Roll, Pitch and Heave in the floater model. Using Maximum Likelihood Estimates and with the eight kinds of regulated distribution functions, the evaluation tests for the CDF having maximum likelihood to the sample data are carried out in this work. Throughout goodness-of-fit tests to the distribution functions, it is shown that the Beta distribution is best-fit to the Roll and Pitch sample data with smallest averaged probability errors $\bar{\delta}(0{\leq}\bar{\delta}{\leq}1.0)$ of 0.024 and 0.022, respectively and, Gamma distribution is best-fit to the Heave sample data with smallest $\bar{\delta}$ of 0.027. The proposed method in this paper can be expected to adopt in various application areas estimating best-fit distributions to the sample data.

• Journal of Bio-Environment Control
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• v.29 no.4
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• pp.414-420
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• 2020

This study was carried out to investigate the growth characteristics of standard chrysanthemum 'Baekma', such as fresh weight, dry weight, and leaf area and to develop prediction models for the production greenhouse based on the growth parameters and climatic elements. Sigmoid regressions models for the prediction of growth parameters in terms of dry weight and leaf area were analyzed according to the number of the day after transplanting and the accumulate temperature during this experimental period. The relative growth rate (RGR) of the chrysanthemum was 0.084 g·g^-1·d^-1 on average during the period.The dry weight and leaf area of 'Beakma' increased exponentially according to the number of day after transplanting and the accumulated temperature, in the case of dry weight increased by an average of 39.1% until 63 days (accumulated temperature of 1601℃), after that dry weight increased by an average of 7.4% before harvest. The leaf area increased by an average of 63.3% until the 28th day after transplanting, and by an average of 6.5% until the 84th day before flower bud differentiation occurred, and increased by an average of 10.6% before harvest. This experiment can be used as a useful data for establishing a cultivation management system and a planned year-round production system for standard chrysanthemum "Baekma". To make a more precise growth prediction model, it will need to be corrected and verified based on various weather data including accumulated irradiation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.142-155
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• 2000

In this paper, we propose an efficient policing mechanism for Markov model-based traffic descriptors of VBR MPEG video traffic. A VBR video sequence is described by a set of traffic descriptors using a scene-basedMarkov model to the network for the effective resource allocation and accurate QoS prediction. The networkmonitors the input traffic from the source using a proposed new policing method. for policing the steady statetransition probability of scene states, we define two representative monitoring parameters (mean holding andrecurrence time) for each state. For frame level cell rate policing of each scene state, accumulated average cellrates for the frame types are compared with the model parameters. We propose an exponential bounding functionto accommodate dynanic behaviors during the transient period. Our simulation results show that the proposedpolicing mechanism for Markovian traffic descriptors monitors the sophisticated traffic such as MPEG videoeffectively and well protects network resources from the nalicious or misbehaved traffic.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.2
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• pp.37-45
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• 2022

A simplified model using the lifetime distribution has been presented to estimate the Mean Residual Life (MRL) of rubble-mound breakwaters, which is not like a stochastic process model based on time-dependent history data to the cumulative damage progress of rubble-mound breakwaters. The parameters involved in the lifetime distribution can be easily estimated by using the upper and lower limits of lifetime and their likelihood that made a judgement by several experts taking account of the initial design lifetime, the past sequences of loads, and others. The simplified model presented in this paper has been applied to the rubble-mound breakwater with TTP armor layer. Wiener Process (WP)-based stochastic model also has been applied together with Monte-Carlo Simulation (MCS) technique to the breakwater of the same condition having time-dependent cumulative damage to TTP armor layer. From the comparison of lifetime distribution obtained from each models including Mean Time To Failure (MTTF), it has found that the lifetime distributions of rubble-mound breakwater can be very satisfactorily fitted by log-normal distribution for all types of cumulative damage progresses, such as exponential, linear, and logarithmic deterioration which are feasible in the real situations. Finally, the MRL of rubble-mound breakwaters estimated by the simplified model presented in this paper have been compared with those by WP stochastic process. It can be shown that results of the presented simplified model have been identical with those of WP stochastic process until any ages in the range of MTT F regardless of the deterioration types. However, a little of differences have been seen at the ages in the neighborhood of MTTF, specially, for the linear and logarithmic deterioration of cumulative damages. For the accurate estimation of MRL of harbor structures, it may be desirable that the stochastic processes should be used to consider properly time-dependent uncertainties of damage deterioration. Nevertheless, the simplified model presented in this paper can be useful in the building of the MRL-based preventive maintenance planning for several kinds of harbor structures, because of which is not needed time-dependent history data about the damage deterioration of structures as mentioned above.