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Applicability of statistical models for risk analyses - a probabilistic model of support systems for prevention of right-turn collisions

机译:统计模型在风险分析中的适用性-预防右转碰撞的支持系统的概率模型

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摘要

In quantitative risk analyses, the top event of fault tree (FT) is originated from basic events through logical causation mechanisms. The occurrences of basic events are often modeled with failure and repair rates with exponential distributions. However, the exponential distribution could not always reflect the reality in some cases where normal or other types of distribution should be adapted. In this paper, Monte Carlo simulations are practiced for the risk estimation of turning to the right collisions caused by automobiles. Comparisons are made between two statistic models, exponential and normal distributions. The result shows the deviation rates are within 10% for those cases. It is concluded that the exponential distribution is applicable to the probabilistic models of FTA where normal distribution would be more suitable.
机译:在定量风险分析中,故障树(FT)的最高事件是通过逻辑因果机制从基本事件中产生的。基本事件的发生通常用具有指数分布的故障率和修复率来建模。但是,在某些情况下,应采用正态分布或其他类型的分布,指数分布不能总是反映现实。在本文中,蒙特卡罗模拟被用于估计由汽车引起的向右碰撞的风险。在两个统计模型(指数分布和正态分布)之间进行了比较。结果表明这些情况下的偏差率在10%以内。结论是,指数分布适用于FTA的概率模型,其中正态分布更适合。

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