• 제목/요약/키워드: Random Demand

검색결과 213건 처리시간 0.022초

터널 화재시 승객의 개인적 위험도 계산에 대한 확률적 접근 (The probability approach for the personal risk calculation of the passenger due to a tunnel fire)

  • 김동진;황영하;장용준
    • 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.

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판매기회가 유실되는 생산/재고 시스템에서의 (s, S) 재고정책 (The (s, S) Policy for Production/Inventory Systems with Lost Sales)

  • 이효성
    • 한국경영과학회지
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    • 제16권1호
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    • pp.13-34
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    • 1991
  • A production/inventory system is considered in which a production facility produces one type of product. The demand for the product is given by a compound Poison process and is supplied directly from inventory when inventory is available and is lost when inventory is out of stock. The processing time to produce one item is assumes to follow a general distribution. An (s, S) policy is considered in which production stops at the instant the stock on hand reachs S and the setup of the production facility begins at an inspection point when the stock on hand drops to or below s for the first time. The time interval between two successive inspection points during a non-production period is a random variable which follows a general distribution.

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Optimal Restocking Policy of an Inventory with Constant Demand

  • Ki, Jeong Jin;Lim, Kyung Eun;Lee, EuiYong
    • Communications for Statistical Applications and Methods
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    • 제11권3호
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    • pp.631-641
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    • 2004
  • In this paper, a model for an inventory whose stock decreases with time is considered. When a deliveryman arrives, if the level of the inventory exceeds a threshold $\alpha$, no stock is delivered, otherwise a delivery is made. It is assumed that the size of a delivery is a random variable Y which is exponentially distributed. After assigning various costs to the model, we calculate the long-run average cost and show that there exist unique value of arrival rate of deliveryman $\alpha$, unique value of threshold $\alpha$ and unique value of average delivery m which minimize the long-run average cost.

자재취급 지연을 고려한 자동창고의 저장능력 추정 (Storage Capacity Estimation for Automated Storage/Retrieval Systems Considering Material Handling Delay)

  • 조면식
    • 한국시뮬레이션학회논문지
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    • 제10권3호
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    • pp.71-82
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    • 2001
  • Considering material handling delay which occurs between storage and processing stations, we propose an algorithm to estimate the required storage capacity, i.e., number of aisles and number of openings in vertical and horizontal directions in each aisle, of an automated storage/retrieval(AS/R) system. Due to the random nature of storage and retrieval requests, proportion of single and dual commands is not known in advance. Two design criteria, maximum permissible overflow probability and maximum allowable storage/retrieval(S/R) machine utilization, are used to compute the storage capacity. Most of studies assume that storage capacity of AS/R systems is given, although it is a very important decision variable in the design phase. Therefore, the proposed model can be effectively used in the design phase of new AS/R systems.

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A probabilistic seismic demand model for required separation distance of adjacent structures

  • Rahimi, Sepideh;Soltani, Masoud
    • Earthquakes and Structures
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    • 제22권2호
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    • pp.147-155
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    • 2022
  • Regarding the importance of seismic pounding, the available standards and guidelines specify minimum separation distance between adjacent buildings. However, the rules in this field are generally based on some simple assumptions, and the level of confidence is uncertain. This is attributed to the fact that the relative response of adjacent structures is strongly dependent on the frequency content of the applied records and the Eigen frequencies of the adjacent structures as well. Therefore, this research aims at investigating the separation distance of the buildings through a probabilistic-based algorithm. In order to empower the algorithm, the record-to-record uncertainties, are considered by probabilistic approaches; besides, a wide extent of material nonlinear behaviors can be introduced into the structural model by the implementation of the hysteresis Bouc-Wen model. The algorithm is then simplified by the application of the linearization concept and using the response acceleration spectrum. By implementing the proposed algorithm, the separation distance in a specific probability level can be evaluated without the essential need of performing time-consuming dynamic analyses. Accuracy of the proposed method is evaluated using nonlinear dynamic analyses of adjacent structures.

Harvest Forecasting Improvement Using Federated Learning and Ensemble Model

  • Ohnmar Khin;Jin Gwang Koh;Sung Keun Lee
    • 스마트미디어저널
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    • 제12권10호
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    • pp.9-18
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    • 2023
  • Harvest forecasting is the great demand of multiple aspects like temperature, rain, environment, and their relations. The existing study investigates the climate conditions and aids the cultivators to know the harvest yields before planting in farms. The proposed study uses federated learning. In addition, the additional widespread techniques such as bagging classifier, extra tees classifier, linear discriminant analysis classifier, quadratic discriminant analysis classifier, stochastic gradient boosting classifier, blending models, random forest regressor, and AdaBoost are utilized together. These presented nine algorithms achieved exemplary satisfactory accuracies. The powerful contributions of proposed algorithms can create exact harvest forecasting. Ultimately, we intend to compare our study with the earlier research's results.

케이프선 시장 운임의 결정요인 및 운임예측 모형 분석 (An Analysis on Determinants of the Capesize Freight Rate and Forecasting Models)

  • 임상섭;윤희성
    • 한국항해항만학회지
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    • 제42권6호
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    • pp.539-545
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    • 2018
  • 운임시장의 심한 변동성과 시계열 데이터의 불안정성으로 해운시황 예측에 대한 연구가 큰 성과를 내지 못하고 있지만 최근 대표적인 비선형 모델인 기계학습모델을 적용한 연구들이 활발히 진행되고 있다. 대부분의 기존 연구가 계량모델의 설계단계에서 입력변수에 해당하는 요인들을 기존 문헌연구와 연구자의 직관에 의존하여 선정했기 때문에 요인선정에 대한 체계적인 연구가 필요하다. 본 연구에서는 케이프선 운임을 대상으로 단계적 회귀모형과 랜덤포레스트모델을 이용하여 중요 영향요인을 분석하였다. 해운시장에서 비교적 단순한 수급구조를 가져 요인파악이 용이한 케이프선 운임을 대상으로 하였으며 총 16개의 수급요인들을 사전 추출하였다. 요인간의 상호관련성을 파악하여 단계적 회귀는 8개 요인, 랜덤포레스트는 10개 요인을 분석대상으로 선정하였으며 선정된 변수를 입력변수로 하여 예측한 결과를 비교하였다. 랜덤포레스트의 예측성능이 아주 우수하였는데 수요요인이 주로 선정된 단계적 회귀분석과는 달리 공급요인이 비중 있게 선정되었기 때문인 것으로 판단된다. 본 연구는 운임예측 연구에 있어 운임결정요인에 대한 과학적인 근거를 마련하였으며 이를 위해 기계학습 기반의 모델을 활용하였다는데 연구적 의의가 있다. 또한 시장정보의 분석에 있어 실무자들이 어떤 변수에 중점을 두어야 하는지에 대해 합리적 근거를 제시한 측면에서 해운기업의 의사결정에 실질적 도움이 될 것으로 기대된다.

E-Business and Simulation

  • Park, Sung-Joo
    • 한국시뮬레이션학회:학술대회논문집
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    • 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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    • pp.9-10
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    • 2001
  • Simulation has been evolved with the advance of computer and technique of modeling application systems. Early simulations were numerical analysis of engineering models known as continuous simulation, analysis of random events using various random number generators thus named as Monte Carlo simulation, iud analysis o(\\\\`queues which are prevalent in many real world systems including manufacturing, transportation, telecommunication. Discrete-event simulation has been used far modeling and analyzing the systems with waiting lines and inefficient delays. These simulations, either discrete-event, continuous, or hybrid, have played a key role in industrial age by helping to design and implement the efficient real world systems. In the information age which has been brought up by the advent of Internet, e-business has emerged. E-business, any business using Internet, can be characterized by the network of extended enterprises---extended supply and demand chains. The extension of value chains spans far reaching scope in business functions and space globally. It also extends to the individual customer, customer preferences and behaviors, to find the best service and product fit for each individual---mass customization. Simulation should also play a key role in analyzing and evaluating the various phenomena of e-business where the phenomena can be characterized by dynamics, uncertainty, and complexity. In this tutorial, applications of simulation to e-business phenomena will be explained and illustrated. Examples are the dynamics of new economy, analysis of e-business processes, virtual manufacturing system, digital divide phenomena, etc. Partly influenced by e-business, a new trend of simulation has emerged called agent-based simulation, Agent-based simulation is a technique of simulation using software agent that have autonomy and proactivity which are useful in analyzing and integrating numerous individual customer's behavior. One particular form of agent-based simulation is swarm. This tutorial concludes with the illustration of swarm or swarm Intelligence applied to various e-business applications, and future directions and implications of this new trend of simulation.

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머신러닝을 활용한 지역축제 방문객 수 예측모형 개발 (Development of a Model to Predict the Number of Visitors to Local Festivals Using Machine Learning)

  • 이인지;윤현식
    • 한국정보시스템학회지:정보시스템연구
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    • 제29권3호
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    • pp.35-52
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    • 2020
  • Purpose Local governments in each region actively hold local festivals for the purpose of promoting the region and revitalizing the local economy. Existing studies related to local festivals have been actively conducted in tourism and related academic fields. Empirical studies to understand the effects of latent variables on local festivals and studies to analyze the regional economic impacts of festivals occupy a large proportion. Despite of practical need, since few researches have been conducted to predict the number of visitors, one of the criteria for evaluating the performance of local festivals, this study developed a model for predicting the number of visitors through various observed variables using a machine learning algorithm and derived its implications. Design/methodology/approach For a total of 593 festivals held in 2018, 6 variables related to the region considering population size, administrative division, and accessibility, and 15 variables related to the festival such as the degree of publicity and word of mouth, invitation singer, weather and budget were set for the training data in machine learning algorithm. Since the number of visitors is a continuous numerical data, random forest, Adaboost, and linear regression that can perform regression analysis among the machine learning algorithms were used. Findings This study confirmed that a prediction of the number of visitors to local festivals is possible using a machine learning algorithm, and the possibility of using machine learning in research in the tourism and related academic fields, including the study of local festivals, was captured. From a practical point of view, the model developed in this study is used to predict the number of visitors to the festival to be held in the future, so that the festival can be evaluated in advance and the demand for related facilities, etc. can be utilized. In addition, the RReliefF rank result can be used. Considering this, it will be possible to improve the existing local festivals or refer to the planning of a new festival.

무작위적인 그래픽 코드를 이용한 인증 알고리즘 (Authentication Algorithm using Random Graphic Code)

  • 정필성;조양현
    • 한국융합학회논문지
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    • 제10권12호
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    • pp.63-69
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    • 2019
  • 스마트폰을 이용하면 쉽고 빠르게 인증과 결제가 가능하다. 하지만 스마트폰 보안 위협이 다양하고 새로운 해킹기술로 진화하고 있고 모바일 환경에 특화된 공격 형태로 변화하고 있다. 따라서 모바일 환경에 적합한 인증방법이 요구되고 있다. 현재 지식기반 인증의 보안 취약점을 해결하기 위한 방법으로 금융, 게임, 로그인 등 인증 서비스를 제공하기 위해서 많은 업체에서 일회용 비밀번호(One Time Password)와 같은 2단계 인증 서비스를 제공하고 있다. OTP 서비스는 사용하기 쉽지만 난수표에 대한 복제가 용이하며 제한시간 내에는 유효한 값으로 사용되기 때문에 재사용이 가능한 단점이 존재한다. 본 논문에서는 스마트폰의 전용 애플리케이션을 통해 특수 문자를 인식한 인증 방법을 이용하여 이용자가 높은 보안성을 가지고 쉽고 빠르게 인증을 진행할 수 있는 매커니즘에 대해서 제안한다.