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Using Fuzzy Expert System Based on Genetic Algorithms for Intrusion Detection System

机译:基于遗传算法的遗传检测系统采用模糊专家系统

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Fuzzy logic based methods together with the techniques from Artificial Intelligence have gained importance. Association rules together with fuzzy logic to model the fuzzy association rules are being used for classifying data. These together with the techniques of genetic algorithms like genetic programming are producing better results. Therefore, in this article, we firstly analyze the current situation of Intrusion Detection Systems, then raise a genetics-based fuzzy system algorithm. In the first stage of this algorithm, it draws initial rules out by using fuzzy algorithm, and in the second stage, the membership function is optimized by the genetic algorithm, with simplification of fuzzy rules, to build a high performance fuzzy system. Finally, we apply this algorithm to the Intrusion Detection System and get a better performance.
机译:基于模糊的逻辑方法与人工智能的技术一起获得了重要性。关联规则与模糊逻辑一起模拟模糊关联规则用于分类数据。这些与基因编程等遗传算法的技术一起产生了更好的结果。因此,在本文中,我们首先分析了入侵检测系统的当前情况,然后提高了一种基于遗传的模糊系统算法。在该算法的第一阶段,它通过使用模糊算法和在第二阶段中绘制初始规则,通过遗传算法优化了隶属算法,以简化模糊规则,构建高性能模糊系统。最后,我们将该算法应用于入侵检测系统并获得更好的性能。

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