• 제목/요약/키워드: Stochastic Network Simulation

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유고상황 시 MatSIM을 활용한 도시부 도로네트워크 운영 분석 (Application of Multi-Agent Transport Simulation for Urban Road Network Operation in Incident Case)

  • 김주영;유연승;이승재;허혜정;성정곤
    • 한국도로학회논문집
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    • 제14권4호
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    • pp.163-173
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    • 2012
  • PURPOSES : The purpose of this study is to check the possibilities of traffic pattern analysis using MatSIM for urban road network operation in incident case. METHODS : One of the stochastic dynamic models is MatSIM. MatSIM is a transportation simulation tool based on stochastic dynamic model and activity based model. It is an open source software developed by IVT, ETH zurich, Switzerland. In MatSIM, various scenario comparison analyses are possible and analyses results are expressed using the visualizer which shows individual vehicle movements and traffic patterns. In this study, trip distribution in 24-hour, traffic volume, and travel speed using MatSIM are similar to those of measured values. Therefore, results of MatSIM are reasonable comparing with measured values. Traffic patterns are changed according to incident from change of individual behavior. RESULTS : The simulation results and the actual measured values are similar. The simulation results show reasonable ranges which can be used for traffic pattern analysis. CONCLUSIONS : The change of traffic pattern including trip distribution, traffic volumes and speeds according to various incident scenarios can be used for traffic control policy decision to provide effective operation of urban road network.

강화학습기법을 이용한 TSP의 해법 (A Learning based Algorithm for Traveling Salesman Problem)

  • 임준묵;배성민;서재준
    • 대한산업공학회지
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    • 제32권1호
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    • pp.61-73
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    • 2006
  • This paper deals with traveling salesman problem(TSP) with the stochastic travel time. Practically, the travel time between demand points changes according to day and time zone because of traffic interference and jam. Since the almost pervious studies focus on TSP with the deterministic travel time, it is difficult to apply those results to logistics problem directly. But many logistics problems are strongly related with stochastic situation such as stochastic travel time. We need to develop the efficient solution method for the TSP with stochastic travel time. From the previous researches, we know that Q-learning technique gives us to deal with stochastic environment and neural network also enables us to calculate the Q-value of Q-learning algorithm. In this paper, we suggest an algorithm for TSP with the stochastic travel time integrating Q-learning and neural network. And we evaluate the validity of the algorithm through computational experiments. From the simulation results, we conclude that a new route obtained from the suggested algorithm gives relatively more reliable travel time in the logistics situation with stochastic travel time.

신뢰도 추정을 위한 분산 학습 신경 회로망 (A variance learning neural network for confidence estimation)

  • 조영빈;권대갑;이경래
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.1173-1176
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    • 1996
  • Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, considering of the stochastic relationship between the data may be very important. The variance is one of the useful parameters to represent the stochastic relationship. This paper presents a new algorithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

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신뢰도 추정을 위한 분산 학습 신경 회로망 (A Variance Learning Neural Network for Confidence Estimation)

  • 조영빈;권대갑
    • 한국정밀공학회지
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    • 제14권6호
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    • pp.121-127
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    • 1997
  • Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, consideration of the stochastic relationship between the input and output data may be very important. Variance is one of the effective parameters to deal with the stochastic relationship. This paper presents a new algroithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

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An Adaptive Radial Basis Function Network algorithm for nonlinear channel equalization

  • Kim Nam yong
    • 한국통신학회논문지
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    • 제30권3C호
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    • pp.141-146
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    • 2005
  • The authors investigate the convergence speed problem of nonlinear adaptive equalization. Convergence constraints and time constant of radial basis function network using stochastic gradient (RBF-SG) algorithm is analyzed and a method of making time constant independent of hidden-node output power by using sample-by-sample node output power estimation is derived. The method for estimating the node power is to use a single-pole low-pass filter. It is shown by simulation that the proposed algorithm gives faster convergence and lower minimum MSE than the RBF-SG algorithm.

확률적 활동 네트워크에서 사업완성시간의 적률 추정: 활동시간의 일반적 분포 (Estimating the Moments of the Project Completion Time in Stochastic Activity Networks: General Distributions for Activity Durations)

  • 조재균
    • 한국산업정보학회논문지
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    • 제23권3호
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    • pp.49-57
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    • 2018
  • Cho는 확률적 활동 네트워크 분석에서 활동시간이 상호 독립적이고 정규분포를 따른다는 가정 하에서 사업완성시간의 적률 (평균, 분산, 왜도, 첨도)을 추정하기 위한 방법을 제안하였다. 본 논문에서는 활동시간의 분포가 일반적인 분포일 때 사업완성시간의 적률을 추정하기 위한 방법을 제안한다. 제안된 방법은 활동시간 분포의 이산화를 위해 적률매칭 방법을 사용하며, 사업완성시간의 계산에 사용될 활동시간을 결정하는데 이산형 역변환 방법을 사용한다. 제안된 방법은 대규모 네트워크에 적용하기 쉽고, 몬테칼로 시뮬레이션 보다 계산적으로 효율적이며, 제안된 방법의 결과는 몬테칼로 시뮬레이션에 의한 결과와 잘 일치함을 보여준다.

STOCHASTIC CASHFLOW MODELING INTEGRATED WITH SIMULATION BASED SCHEDULING

  • Dong-Eun Lee;David Arditi;Chang-Baek Son
    • 국제학술발표논문집
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    • The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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    • pp.395-398
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    • 2011
  • This paper introduces stochastic cash-flow modeling integrated with simulation based scheduling. The system makes use of CPM schedule data exported from commercial scheduling software, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, simulates the schedule network, computes the deterministic and stochastic project cash-flows, plots the corresponding cash flow diagrams, and estimates the best fit PDFs of overdraft and net profit of a project. It analyzes the effect of different distributions of activity durations on the distribution of overdrafts and net profits, and improves reliability compared to deterministic cash flow analysis.

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IMPROVING THE USABILITY OF STOCHASTIC SIMULATION BASED SCHEDULING SYSTEM

  • Tae-Hyun Bae;Ryul-Hee Kim;Kyu-Yeol Song;Dong-Eun Lee
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.393-399
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    • 2009
  • This paper introduces an automated tool named Advanced Stochastic Schedule Simulation System (AS4). The system automatically integrates CPM schedule data exported from Primavera Project Planner (P3) and historical activity duration data obtained from a project data warehouse, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, computes the optimum number of simulation runs, simulates the schedule network for the optimum number of simulation runs, and estimates the best fit PDF of project completion times (PCTs). AS4 improves the reliability of simulation-based scheduling by effectively dealing with the uncertainties of the activities' durations, increases the usability of the schedule data obtained from commercial CPM software, and effectively handles the variability of the PCTs by finding the best fit PDF of PCTs. It is designed as an easy-to-use computer tool programmed in MATLAB. AS4 encourages the use of simulation-based scheduling because it is simple to use, it simplifies the tedious and burdensome process involved in finding the PDFs of the many activities' durations and in assigning the PDFs to the many activities of a new network under modeling, and it does away with the normality assumptions used by most simulation-based scheduling systems in modeling PCTs.

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확률적 네트워크의 신뢰도 평가를 위한 분산 감소기법의 응용 (An Application of Variance Reduction Technique for Stochastic Network Reliability Evaluation)

  • 하경재;김원경
    • 한국시뮬레이션학회논문지
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    • 제10권2호
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    • pp.61-74
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    • 2001
  • The reliability evaluation of the large scale network becomes very complicate according to the growing size of network. Moreover if the reliability is not constant but follows probability distribution function, it is almost impossible to compute them in theory. This paper studies the network evaluation methods in order to overcome such difficulties. For this an efficient path set algorithm which seeks the path set connecting the start and terminal nodes efficiently is developed. Also, various variance reduction techniques are applied to compute the system reliability to enhance the simulation performance. As a numerical example, a large scale network is given. The comparisons of the path set algorithm and the variance reduction techniques are discussed.

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클리스터 기반 연속 미디어 저장 서버에서의 통합형 통계적 승인 제어 기법 (Integrated Stochastic Admission Control Policy in Clustered Continuous Media Storage Server)

  • 김영주;노영욱
    • 정보처리학회논문지A
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    • 제8A권3호
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    • pp.217-226
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    • 2001
  • 본 논문은 클러스터 기반의 분산 구조를 갖는 CCMSS(Clustered Continuous Media Storage Server) 시스템의 미디어 검색 동작에 대해 디스크의 입출력 지연 시간 뿐맘 아니라 내부 네트워크의 통신 지연 시간을 함께 고려한, 열린 큐잉 네트워크 기반의 해석적 모델을 제시하고 이를 이용하여 전체 서비스 지연 시간에 대한 확률적 모델을 정의한다. 그리고 정의된 확률적 모델을 바탕으로 허용된 서비스 실패율 범위에서 최대 서비스 가능한 사용자 요구 수를 구하고 이 값을 이용하여 승인 제어를 수행하는 통합형 통계적 승인 제어 모델을 제안한다. 제안된 승인 제어 기법의 성능 분석을 위해 단순히 디스크 성능만을 고려한 확률적 모델과 본 논문에서 제안한 디스크 성능과 내부 네트워크의 성능을 함께 고려한 확률적 모델을 통해 산출한 마감시간 실패율과 실제 클러스터 기반 서버 환경에서 모의 실험을 통해 얻은 결과를 비교하였으며, 실험 결과에 대한 분석을 통해 제안된 승인 제어 기법이 CCMSS 시스템의 실제 서비스 지연 요소를 정확히 반영하고 있다는 것을 알 수 있었다.

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