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Events group risk importance by genetic algorithms

机译:事件组风险重要性的遗传算法

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摘要

In this paper, the power of genetic algorithms is exploited to search for the most important groups of events in a risk/reliability model. To this end a two-objective search is formulated in which the decision variables are the groups of events, and the objectives are to maximize the importance of the groups, while minimizing their dimension. This allows the identification of the most important single events, couples of events, triplets, and so forth. Three case studies concerning network systems of increasing complexity are analysed.
机译:在本文中,利用遗传算法的功能来搜索风险/可靠性模型中最重要的事件组。为此,制定了两个目标的搜索,其中决策变量是事件的组,目标是在最大程度地减小组的同时最大程度地减小组的重要性。这样可以识别最重要的单个事件,事件对,三胞胎等。分析了有关网络系统日益复杂的三个案例研究。

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