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Transforming Renewal Processes for Simulation of Nonstationary Arrival Processes

机译:转换更新过程以模拟非平稳到达过程

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Simulation models of real-life systems often assume stationary (homogeneous) Poisson arrivals. Therefore, when nonstationary arrival processes are required, it is natural to assume Poisson arrivals with a time-varying arrival rate. For many systems, however, this provides an inaccurate representation of the arrival process that is either more or less variable than Poisson. In this paper we extend techniques that transform a stationary Poisson arrival process into a nonstationary Poisson arrival process (NSPP) by transforming a stationary renewal process into a nonstationary, non-Poisson (NSNP) arrival process. We show that the desired arrival rate is achieved and that when the renewal base process is either more or less variable than Poisson, then the NSNP process is also more or less variable, respectively, than an NSPP. We also propose techniques for specifying the renewal base process when presented properties of, or data from, an arrival process and illustrate them by modeling real arrival data.
机译:现实生活中的系统的仿真模型通常假定泊松平稳(均匀)到达。因此,当需要非平稳到达过程时,自然会假设泊松到达具有随时间变化的到达速率。但是,对于许多系统而言,这提供了一个不精确的到达过程表示,该过程比Poisson或多或少具有可变性。在本文中,我们通过将静态更新过程转换为非平稳非泊松(NSNP)到达过程,扩展了将静态泊松到达过程转换为非平稳Poisson到达过程(NSPP)的技术。我们表明,达到了所需的到达率,并且当续订基础流程比Poisson或多或少可变时,则NSNP流程也比NSPP或多或少可变。当提出的到达过程的属性或来自到达过程的数据时,我们还提出了用于指定更新基础过程的技术,并通过对实际到达数据进行建模来说明它们。

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