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Using qualitative discrete event simulation to calculate near exact output statistics.

机译：使用定性离散事件模拟来计算接近精确的输出统计信息。

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摘要

Scope and method of study. The scope of this dissertation is to develop a statistical analysis method for the Qualitative Discrete Event Simulation (QDES) methodology. The method presented shows the calculation of the probability of occurrence and the event time distribution for each event that is generated using QDES by imposing an assumption on the distribution of the delay intervals in the simulation, in particularly uniform distribution. The resulting calculations are used in calculating the simulation time-persistent output statistics and tally statistics for variables of interests.;Findings and conclusions. The Qualitative Discrete Event Simulation (QDES) methodology has been advanced as a decision tool and its capability has been enhanced to provide meaningful output information. A probabilistic approach to the statistical analysis of a QDES model has been developed. The advancement in the area of reasoning with probability to produce near exact output statistics from QDES will allow modelers to make wise decisions based on a single run, instead of sampling from multiple runs as in a regular discrete event simulation model. The near exact output statistics will be able to describe the distribution of different variables, such as the queue length, customer delay, server utilization, etc., together with information for the probability of these average values occurring for each variable and the event sequences that lead to these values. The probabilistic nature of our approach to calculating statistics from a QDES output opens up new chapter on creating a closed-form discrete event simulation output. The key behind the approach is that by imposing statistical distribution on the temporal intervals and using a complex set of conditional probabilities for the thread, the statistics in the QDES model is exactly represented.
机译：研究范围和方法。本文的研究范围是为定性离散事件模拟（QDES）方法开发一种统计分析方法。提出的方法通过对模拟中延迟间隔的分布（尤其是均匀分布）进行假设，从而显示了使用QDES生成的每个事件的发生概率和事件时间分布的计算。结果计算将用于计算仿真持续时间的输出统计量和感兴趣变量的计数统计量。结果和结论。定性离散事件模拟（QDES）方法已作为一种决策工具得到了改进，其功能得到了增强，可以提供有意义的输出信息。已经开发出一种概率方法对QDES模型进行统计分析。推理领域的进展可能会从QDES产生接近准确的输出统计数据，这将使建模人员能够基于单次运行做出明智的决策，而不是像常规的离散事件模拟模型那样从多次运行中进行采样。几乎精确的输出统计信息将能够描述不同变量的分布，例如队列长度，客户延迟，服务器利用率等，以及有关每个变量出现这些平均值的概率信息以及事件序列。导致这些价值。我们从QDES输出计算统计信息的方法的概率性质为创建封闭形式的离散事件模拟输出开辟了新篇章。该方法背后的关键是，通过在时间间隔上施加统计分布，并对线程使用一组复杂的条件概率，可以精确表示QDES模型中的统计信息。

著录项

  • 作者

    Leow, Yen Ping.;

  • 作者单位

    Oklahoma State University.;

  • 授予单位 Oklahoma State University.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:39:29

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