• 응용통계연구
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• 제36권1호
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• pp.49-62
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• 2023

급속적으로 비중이 증가하고 있는 태양광 에너지는 지속적인 개발 및 투자가 이루어지고 있다. 신재생에너지 정책인 그린뉴딜과 가정용 태양광 패널의 설치가 증가함에 따라 국내 태양광 에너지 보급이 점차 확대되어 그에 맞추어 발전량의 정확한 수요 예측 연구가 활발하게 진행되고 있는 시점이다. 또한, 일사량 예측이 발전량 수요 예측에 가장 영향을 미치는 요소로 작용하고 있다는 점에서 일사량 예측의 중요성을 파악하였다. 덧붙여, 본 연구는 선행 연구들에서 사용되지 않은 중기예보 기상 데이터를 활용하여 일사량 예측을 하고자 하였다는 점에서 가장 큰 차이점을 확인할 수 있다. 본 논문에서는 서울, 인천, 수원, 춘천, 대구, 대전의 총 여섯 지역의 태양광 일사량 예측을 위하여 다중선형회귀모형, KNN, Random Forest 그리고 SVR 모형과 클러스터링 기법인 K-means 기법을 결합한 후, 클러스터별 확률밀도함수를 계산하여 시간별 일사량 예측을 진행하고자 하였다. 중기예보 데이터를 사용하기 전, 모형 예측 결과를 비교하기 위한 지표로서 MAE (mean absolute error)와 RMSE (root mean squared error)를 사용하였다. 데이터는 2017년 3월 1일부터 2022년 2월 28일까지의 시간별 원 관측 데이터를 중기예보 데이터 양식에 맞추어 일별 데이터로 변환하였다. 모형의 예측 성능 비교 결과, Random Forest로 일별 일사량을 예측한 후, K-means 클러스터링으로 기후요인이 유사한 날짜들을 분류한 뒤 클러스터별 일사량의 확률밀도함수를 계산하여 시간별 일사량 예측값을 나타낸 방법이 가장 우수한 성능을 보였다. 또한 이 방법론을 이용하여 중기예보 데이터에 모형 적합 후, 예측 결과를 확인하였을 때, 일자별로 예측 오류가 상승하는 것을 확인할 수 있었다. 이는 중기예보 기상데이터의 예측 오류로 인한 것으로 보인다. 향후 연구에서는 중기예보 데이터에서 활용할 수 있는 기상요인 중, 강수 여부와 같은 외생 변수를 추가하거나 시계열 클러스터링 기법을 적용한 연구가 이루어져야할 것으로 보인다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.293-298
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• 1993

In ground vehicles, the increasing demand for safety and ride comfort which are trade-off relation, especially at high speeds, has led to the development od actively controlled suspensions. The LQG/LTR controller can be used to design a robust feedback control system that deals with disturbance rejection properties as well as insensitivity to modelling errors and sensor noise. And when the disturbance can not be measured but is limited within a certain frequency range, a bandpass feedback to eliminate the disturbance response can be used. In this paper, hybrid controller cosisted of bandpass feedback controller and LQG/LTR controller is applied to a quarter-car model moving on a randomly profiled road. The random road profile considered as colored noise is shaped from white noise by use of shaping filter. The performance of the hybrid control system is compared with that of an LQG/LTR controlled system.

• 대한산업공학회지
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• 제12권1호
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• pp.43-48
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• 1986

In this paper, the one period multi-item inventory model is considered in which it is required to determine the production quantity and selling price of each item which maximize the probability of realizing predetermined level of profit. The objective function of this model is the sum of weighted probabilities which represent the possibility of obtaining the predetermined level of profit for each item. Budget constraint, inventory site constraint and constraints of price are considered. Finally this paper shows a numerical example in which random demand of each item has exponential distribution.

• 품질경영학회지
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• 제30권3호
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• pp.53-65
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• 2002

This paper studies an economic manufacturing quantity (EMQ) model with two types of failures and planned preventive maintenance of the production facility. One is a type I (major) failure which should be corrected by a failure maintenance and the other is a type H (minor) failure which can be minimally repaired without interrupting the production run. The objective is to determine the lot size and preventive replacement policy minimizing the long-run expected cost per unit time. We consider a control policy with a constant production lot size and preventive maintenance after completing n production runs. It is assumed that both preventive and failure maintenance times are random and the demand arriving during a stock-out period is lost. An expression for the expected cost per unit time is obtained in the general case. A special case is discussed and numerical results are provided.

• 대한산업공학회지
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• 제24권1호
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• pp.137-144
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• 1998

Block stacking, which involves the storage of unit loads in stacks within storage rows, is typically used in traditional warehouses to achieve a high space utilization at a low investment cost. In this paper, assuming that the demand size from a customer is an i.i.d. random variable, we develop a probabilistic block stacking storage model and its algorithm for a singles product, which minimizes the time-overage floor space requirement under an (s, S) inventory policy and the violation of the FIFO lot rotation rule only in a single partially-occupied row.

• International Journal of Precision Engineering and Manufacturing
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• 제1권1호
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• pp.49-55
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• 2000

The semiconductor industry relies on digital optical imaging for the overlay metrology of integrated circuit patterns. One critical performance demand in the particular application of digital imaging is placed on the edge resolution that is defined as the smallest detectable displacement of an edge from its image acquired in digital from. As the critical feature size of integrated circuit patterns reaches below 0.35 micrometers, the edge resolution is required to be less than 0.01 micrometers. This requirement is so stringent that fundamental behaviors of digital optical imaging need to be explored especially for the precision coordinate metrology. Our investigation reveals that the edge resolution shows quasi-random characteristics, not being simply deduced from relevant opto-electronic system parameters. Hence, a stochastic upper bound analysis is made to come up with the worst edge resolution that can statistically well predict actual indeterminate edge resolutions obtained with high magnification microscope objectives.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.377-383
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• 2020

The likelihood-based inference in a nonlinear generalized mixed model often requires computing moments of truncated multivariate normal random variables. Many methods have been proposed for the computation using a recurrence relation or the moment generating function; however, these methods rely on high dimensional numerical integrations. The numerical method is known to be inefficient for high dimensional integral in accuracy. Besides the accuracy, the methods demand too much computing time to use them in practical analyses. In this note, a moment calculation method is proposed under an assumption of a certain covariance structure that occurred mostly in generalized mixed models. The method needs only low dimensional numerical integrations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.3171-3191
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• 2016

Due to growing demand on wireless data traffic, a large number of different types of base stations (BSs) have been installed. However, space-time dependent wireless data traffic densities can result in a significant number of idle BSs, which implies the waste of power resources. To deal with this problem, we propose an active state control algorithm based on semi-Markov decision process (SMDP) for a heterogeneous network. A MDP in discrete time domain is formulated from continuous domain with some approximation. Suboptimal on-line learning algorithm with a random policy is proposed to solve the problem. We explicitly include coverage constraint so that active cells can provide the same signal to noise ratio (SNR) coverage with a targeted outage rate. Simulation results verify that the proposed algorithm properly controls the active state depending on traffic densities without increasing the number of handovers excessively while providing average user perceived rate (UPR) in a more power efficient way than a conventional algorithm.

• Structural Engineering and Mechanics
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• 제9권6호
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• pp.557-568
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• 2000

As time-variant reliability approaches become increasingly used for service life prediction of the aging infrastructure, the demand for computer solution methods continues to increase. Effcient computer techniques have become well established for the reliability analysis of structural systems. Thus far, however, this is largely limited to time-invariant reliability problems. Therefore, the requirements for time-variant reliability prediction of deteriorating structural systems under time-variant loads have remained incomplete. This study presents a computer program for $\underline{REL}$iability of $\underline{T}$ime-Variant $\underline{SYS}$tems, RELTSYS. This program uses a combined technique of adaptive importance sampling, numerical integration, and fault tree analysis to compute time-variant reliabilities of individual components and systems. Time-invariant quantities are generated using Monte Carlo simulation, whereas time-variant quantities are evaluated using numerical integration. Load distribution and post-failure redistribution are considered using fault tree analysis. The strengths and limitations of RELTSYS are presented via a numerical example.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.1246-1254
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• 2008

The land transportation is the most common way to transport passengers as well as freight among other mode of transportations and consequently more likely to be constructed for faster and convenient travel In this regard, the demand for tunnel constructions will be increasing and the safety inside the tunnel will be considered major concern more than ever. In this paper, we show probabilistic methodology to calculate the personal risk of each evacuee starting from a different location in a tunnel on fire. Passenger evacuation time and smoke spread time are both assumed to be continuous random variables having specific distributions. The evacuation of passengers at each location and the safety facilities inside the tunnel are also crucial factors to calculate the probability of death.