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A novel Artificial Immune System for fault behavior detection

机译:一种用于故障行为检测的新型人工免疫系统

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This paper presents an error detection methodology to enable fault detection inspired on recent immune theory. The fault detection problem is a challenging problem due to processes increasing complexity and agility necessary to avoid malfunction or accidents. The key challenge is determining the difference between normal and potential harmful activities. A promising solution is emerging in the form of Artificial Immune System (AIS). In this article, Natural Killer (NK) immune cells mechanisms inspired an AIS. The AIS proposed uses recent biological mechanism such as: NK activation and education machinery. DAMADICS benchmark was applied to compare the proposed AIS performance to others fault detection algorithms. The results show that the novel approach developed provides better detection rate and false alarms tradeoff when compared to other methods in literature.
机译:本文提出了一种错误检测方法,可以根据最新的免疫理论来实现故障检测。由于过程增加了避免故障或事故所必需的复杂性和敏捷性,因此故障检测问题是具有挑战性的问题。关键的挑战是确定正常和潜在有害活动之间的区别。一种有希望的解决方案正在以人工免疫系统(AIS)的形式出现。在本文中,自然杀手(NK)免疫细胞机制激发了AIS。提议的AIS使用了最新的生物学机制,例如:NK激活和教育机制。使用DAMADICS基准测试将AIS的性能与其他故障检测算法进行比较。结果表明,与文献中的其他方法相比,开发的新方法提供了更好的检测率和虚假警报权衡。

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