• 제목/요약/키워드: Poisson Distribution

검색결과 585건 처리시간 0.026초

Stochastic ship roll motion via path integral method

  • Cottone, G.;Paola, M. Di;Ibrahim, R.;Pirrotta, A.;Santoro, R.
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제2권3호
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    • pp.119-126
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    • 2010
  • The response of ship roll oscillation under random ice impulsive loads modeled by Poisson arrival process is very important in studying the safety of ships navigation in cold regions. Under both external and parametric random excitations the evolution of the probability density function of roll motion is evaluated using the path integral (PI) approach. The PI method relies on the Chapman-Kolmogorov equation, which governs the response transition probability density functions at two close intervals of time. Once the response probability density function at an early close time is specified, its value at later close time can be evaluated. The PI method is first demonstrated via simple dynamical models and then applied for ship roll dynamics under random impulsive white noise excitation.

Bootstrap Inference on the Poisson Rates for Grouped Data

  • Lee, Kee-Won;Kim, Woo-Chul
    • Journal of the Korean Statistical Society
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    • 제30권1호
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    • pp.1-20
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    • 2001
  • We present how bootstrap methods can be used to conduct inference on the rates of Poisson distributions when only the grouped data are available. A theoretical justification for the validity of bootstrap is given with an illustration of proposed method using a data set obtained fro ma pathology laboratory test. Traditional asymptotic methods are compared with bootstrap methods in computing the estimated standard errors and achieved significance levels for one sample and two sample tests. Bootstrap methods are shown to possess a nice property that he small sample distribution of the relevant statistics can be readily obtained from the bootstrap copies.

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Analytical Modeling and Simulation of Dual Material Gate Tunnel Field Effect Transistors

  • Samuel, T.S.Arun;Balamurugan, N.B.;Sibitha, S.;Saranya, R.;Vanisri, D.
    • Journal of Electrical Engineering and Technology
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    • 제8권6호
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    • pp.1481-1486
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    • 2013
  • In this paper, a new two dimensional (2D) analytical model of a Dual Material Gate tunnel field effect transistor (DMG TFET) is presented. The parabolic approximation technique is used to solve the 2-D Poisson equation with suitable boundary conditions. The simple and accurate analytical expressions for surface potential and electric field are derived. The electric field distribution can be used to calculate the tunneling generation rate and numerically extract tunneling current. The results show a significant improvement of on-current and reduction in short channel effects. Effectiveness of the proposed method has been confirmed by comparing the analytical results with the TCAD simulation results.

복합포아송 수요를 갖는 CONWIP 시스템의 주문관점에서의 성능평가 (Order Based Performance Evaluation of a CONWIP System with Compound Poisson Demands)

  • 박찬우;이효성
    • 한국경영과학회지
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    • 제32권1호
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    • pp.137-146
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    • 2007
  • In this study we consider a CONWIP system studied in Park and Lee [1] in which the processing times at each station follow a Coxian distribution and the demands for the finished products arrive according to a compound Poisson process. The demands that are not satisfied Immediately are either backordered or lost according to the number of demands that exist at their arrival instants. For this system using the results in [1] we develop an approximation method to calculate order based performance measures such as the mean time of fulfilling a customer order and the mean number of customer orders. To test the accuracy of the approximation method, the results obtained from the approximation method are compared with those obtained by simulation. Comparisons with simulation have shown that the approximate method provides fairly good results.

순간전압강하 모니터링 데이터 분석 방법 (Development of a Method to Analyze Voltage Sag Monitoring Data)

  • 박창현
    • 조명전기설비학회논문지
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    • 제27권4호
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    • pp.16-22
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    • 2013
  • This paper presents a method to analyze the voltage sag data obtained from monitoring systems. In order to establish effective countermeasures against voltage sag problems, an assessment of the system performance with respect to voltage sags is needed. Generally, the average annual sag frequency can be estimated by using the recorded voltage sag events for several years. However, the simple average value can not give the information about the errors of estimation. Such an average estimation is not useful for establishing effective solutions for voltage sag problems. Therefore, this paper proposes an effective method based on the Interval Estimation method. The estimation of voltage sag frequency is performed by using the average frequency and Poisson probability model. The proposed method can give the expected annual sag frequency and upper one-sided bound frequency.

An Analytical Modeling and Simulation of Dual Material Double Gate Tunnel Field Effect Transistor for Low Power Applications

  • Arun Samuel, T.S.;Balamurugan, N.B.
    • Journal of Electrical Engineering and Technology
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    • 제9권1호
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    • pp.247-253
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    • 2014
  • In this paper, a new two dimensional (2D) analytical modeling and simulation for a Dual Material Double Gate tunnel field effect transistor (DMDG TFET) is proposed. The Parabolic approximation technique is used to solve the 2-D Poisson equation with suitable boundary conditions and analytical expressions for surface potential and electric field are derived. This electric field distribution is further used to calculate the tunnelling generation rate and thus we numerically extract the tunnelling current. The results show a significant improvement in on-current characteristics while short channel effects are greatly reduced. Effectiveness of the proposed model has been confirmed by comparing the analytical results with the TCAD simulation results.

지수형과 로그형 위험함수 학습효과에 근거한 NHPP 소프트웨어 신뢰성장모형에 관한 비교연구 (The Comparative Study of NHPP Software Reliability Model Exponential and Log Shaped Type Hazard Function from the Perspective of Learning Effects)

  • 김희철
    • 디지털산업정보학회논문지
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    • 제8권2호
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    • pp.1-10
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    • 2012
  • In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.

A Queueing System with Work-Modulated Arrival and Service Rates

  • Lee, Jiyeon
    • Journal of the Korean Statistical Society
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    • 제28권1호
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    • pp.125-133
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    • 1999
  • We consider a FIFO single-server queueing model in which both the arrival and service processes are modulated by the amount of work in the system. The arrival process is a non-homogeneous Poisson process(NHPP) modulated by work, that is, with an intensity that depends on the work in the system. Each customer brings a job consisting of an exponentially distributed amount of work to be processed. The server processes the work at various service rates which also depend on the work in the system. Under the stability conditions obtained by Browne and Sigman(1992) we derive the exact stationary distribution of the work W(t) and the first exit probability that the work level b is exceeded before the work level a is reached, starting from x$\in$[a, b].

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Flows and Some Extreme Values in Multiple Server Open Jackson network

  • Park, You-Sung;Lee, Hae-Yong
    • Journal of the Korean Statistical Society
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    • 제24권2호
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    • pp.389-405
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    • 1995
  • Output processes emanating from exit arcs in a mulitple server open Jackson network with node i having $s_i$ servers are determined. Beutler and Melamed (1978) showed, for traffics on all exit arcs of single server open Jackson network in equilibrium, that the customer streams leaving any exit set are Poisson and that the collections over all nodes which yield the Poisson departure processes are mutually independent. In this paper we generalize the above results to multiple servers open Jackson network in equilibrium. While no weak limit result is possible under the equilibrium condition, nonetheless approximations to the distributions of maximum queue lengths for no feedback nodes in multiple servers open Jackson network are established.

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혼합 와이블 NHPP 모형에 근거한 소프트웨어 최적방출시기에 관한 연구 (A Study on Optimal Release Time for Software Systems based on Mixture Weibull NHPP Model)

  • 이상식;김희철
    • 디지털산업정보학회논문지
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    • 제6권2호
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    • pp.183-191
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    • 2010
  • Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used mixture which has various intensity, if the system is complicated. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.