• 제목/요약/키워드: Markov Processes

검색결과 143건 처리시간 0.021초

용량 확장과 반납을 갖는 렌탈 자원 관리모델 (Rental Resource Management Model with Capacity Expansion and Return)

  • 김은갑;변진호
    • 한국경영과학회지
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    • 제31권3호
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    • pp.81-96
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    • 2006
  • We consider a rental company that dynamically manages Its capacity level through capacity addition and return While serving customer with its own capacity, the company expands its capacity by renting items from an outside source so that it can avoid lost opportunities of rental which occur when stock is not sufficient. If stock becomes sufficiently large enough to cope with demands, the company returns expanded capacity to the outside source. Formulating the model into a Markov decision problem, we identify an optimal capacity management Policy which states when the company should expand its capacity and when it should return expanded capacity after capacity addition. Since it is intractable to analytically find the optimal capacity management policy and the optimal size of capacity expansion, we present a numerical procedure that finds these optimal values based on the value iteration method. Numerical analysis is implemented and we observe monotonic properties of the optimal performance measures by system parameters, which are meaningful in developing effective heuristic policies.

두 계층 공급사슬 모형에서 발주정책에 대한 수요 변동성 영향 (Demand Variability Impact on the Replenishment Policy in a Two-Echelon Supply Chain Model)

  • 김은갑
    • 한국경영과학회지
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    • 제29권3호
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    • pp.111-127
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    • 2004
  • We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

인간의 움직임 추출을 이용한 감정적인 행동 인식 시스템 개발 (Emotional Human Body Recognition by Using Extraction of Human Body from Image)

  • 송민국;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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    • pp.214-216
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    • 2006
  • Expressive face and human body gestures are among the main non-verbal communication channels in human-human interaction. Understanding human emotions through body gesture is one of the necessary skills both for humans and also for the computers to interact with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. Skin color information for tracking hand gesture is obtained from face detection region. We have revealed relationships between paricular body movements and specific emotions by using HMM(Hidden Markov Model) classifier. Performance evaluation of emotional human body recognition has experimented.

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고장감지장치를 고려한 수리가능 시스템의 신뢰도 분석 (Reliability Analysis of Repairable Systems Considering Failure Detection Equipments)

  • 나성룡
    • 응용통계연구
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    • 제24권3호
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    • pp.515-521
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    • 2011
  • 이 논문에서는 수리가능한 시스템의 고장을 감지해서 수리 개시를 가능하게 하는 고장감지장치를 고려한 시스템 신뢰도 산출을 연구한다. 실제 상황에서 고장감지장치의 고장이 가능할 수 있는데 이는 시스템 고장의 미발견을 초래할 수 있고 시스템 신뢰도에 큰 영향을 주게 된다. 적절한 마코프 확률과정을 이용하여 감지장치의 고장이 가져오는 시스템 신뢰도에 대한 영향을 분석한다.

A GAUSSIAN WHITE NOISE GENERATOR AND ITS APPLICATION TO THE FLUCTUATION-DISSIPATION FORMULA

  • Moon, Byung-Soo
    • Journal of applied mathematics & informatics
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    • 제15권1_2호
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    • pp.363-375
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    • 2004
  • In this paper, We show that the bandpass random signals of the form ∑$_{\alpha}$$\alpha$$_{\alpha}$ a Sin(2$\pi$f$_{\alpha}$t + b$_{\alpha}$) where a$_{\alpha}$ being a random number in [0,1], f$_{\alpha}$ a random integer in a given frequency band, and b$_{\alpha}$ a random number in [0, 2$\pi$], generate Gaussian white noise signals and hence they are adequate for simulating Continuous Markov processes. We apply the result to the fluctuation-dissipation formula for the Johnson noise and show that the probability distribution for the long term average of the power of the Johnson noise is a X$^2$ distribution and that the relative error of the long term average is (equation omitted) where N is the number of blocks used in the average.error of the long term average is (equation omitted) where N is the number of blocks used in the average.

정책 기울기 값 강화학습을 이용한 적응적인 QoS 라우팅 기법 연구 (A Study of Adaptive QoS Routing scheme using Policy-gradient Reinforcement Learning)

  • 한정수
    • 한국컴퓨터정보학회논문지
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    • 제16권2호
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    • pp.93-99
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    • 2011
  • 본 논문에서는 강화학습(RL : Reinforcement Learning) 환경 하에서 정책 기울기 값 기법을 사용하는 적응적인 QoS 라우팅 기법을 제안하였다. 이 기법은 기존의 강화학습 환경 하에 제공하는 기법에 비해 기대 보상값의 기울기 값을 정책에 반영함으로써 빠른 네트워크 환경을 학습함으로써 보다 우수한 라우팅 성공률을 제공할 수 있는 기법이다. 이를 검증하기 위해 기존의 기법들과 비교 검증함으로써 그 우수성을 확인하였다.

인플루엔자 유행의 마르코프 모델 해석 (Markovian Model Analysis of Influenza System)

  • 정형환;김권수
    • 대한전기학회논문지
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    • 제33권11호
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    • pp.440-446
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    • 1984
  • This thesis investigates the quantitative aspect of epidemic phenomena utilizing the analytical method of discrete time systems based on the theory of Markov processes. In particular, the pattern on the epidemic character of Influenza was analyzed by the mathematical model of Influenza system, which is derived according to the ecologic relationship between five epidemiolgic states of individuals. The quantitative aspects of the model was characterized by digital computer simulations. The main results were obtained as follows: 1) A Markovian model of influenza system represents accurate spead curve. 2) The latent period of influenza has the standard deviation of 1.98 and also the incubation period is 2.68. 3) If the value of susceptibilities in the pre-epidemic period is less than 20% of the population, the epidemic will occur sporadically. 4) The initial value of susceptibilties obtained by this markov theory is less about 10% of total population than the obtained value according to the deterministic model.

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A Combined Process Control Procedure by Monitoring and Repeated Adjustment

  • Park, Changsoon
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.773-788
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    • 2000
  • Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for processes quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation. while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been needs for a process control proceduce which combines the tow strategies. This paper considers a combined scheme which simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an integrated moving average(IMA) process with a step shift. The EPC part of the scheme adjusts the process back to target at every fixed monitoring intervals, which is referred to a repeated adjustment scheme. The SPC part of the scheme uses an exponentially weighted moving average(EWMA) of observed deviation from target to detect special causes. A Markov chain model is developed to relate the scheme's expected cost per unit time to the design parameters of he combined control scheme. The expected cost per unit time is composed of off-target cost, adjustment cost, monitoring cost, and false alarm cost.

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Seamless Mobility of Heterogeneous Networks Based on Markov Decision Process

  • Preethi, G.A.;Chandrasekar, C.
    • Journal of Information Processing Systems
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    • 제11권4호
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    • pp.616-629
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    • 2015
  • A mobile terminal will expect a number of handoffs within its call duration. In the event of a mobile call, when a mobile node moves from one cell to another, it should connect to another access point within its range. In case there is a lack of support of its own network, it must changeover to another base station. In the event of moving on to another network, quality of service parameters need to be considered. In our study we have used the Markov decision process approach for a seamless handoff as it gives the optimum results for selecting a network when compared to other multiple attribute decision making processes. We have used the network cost function for selecting the network for handoff and the connection reward function, which is based on the values of the quality of service parameters. We have also examined the constant bit rate and transmission control protocol packet delivery ratio. We used the policy iteration algorithm for determining the optimal policy. Our enhanced handoff algorithm outperforms other previous multiple attribute decision making methods.

A SHARP BOUND FOR ITO PROCESSES

  • Choi, Chang-Sun
    • 대한수학회지
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    • 제35권3호
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    • pp.713-725
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    • 1998
  • Let X and Y be Ito processes with dX$_{s}$ = $\phi$$_{s}$dB$_{s}$$\psi$$_{s}$ds and dY$_{s}$ = (equation omitted)dB$_{s}$ + ξ$_{s}$ds. Burkholder obtained a sharp bound on the distribution of the maximal function of Y under the assumption that │Y$_{0}$$\leq$│X$_{0}$│,│ζ│$\leq$$\phi$│, │ξ│$\leq$$\psi$│ and that X is a nonnegative local submartingale. In this paper we consider a wider class of Ito processes, replace the assumption │ξ│$\leq$$\psi$│ by a more general one │ξ│$\leq$$\alpha$$\psi$│ , where a $\geq$ 0 is a constant, and get a weak-type inequality between X and the maximal function of Y. This inequality, being sharp for all a $\geq$ 0, extends the work by Burkholder.der.urkholder.der.

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