The experimental results show that the proposed fuzzy classifier based on AFS theory and Genetic Algorithm has few rules, high classification rate, and good interpretability.
从实验结果可以看出将两者结合设计出的模糊分类器具有分类准确率高、模糊描述简单、规则少且易于理解等特点。
This genetic-fuzzy classifier based on fuzzy associative rules can make accurate judgments without enough evidence to improve the performance of the IDS.
该模型在证据不充分的情况下能够更快速、正确地判断入侵事件，从而进一步提高检测的效率。
This genetic-fuzzy classifier based on fuzzy associative rules can make accurate judgments without enough evidence to improve the performance of the IDS.
该模型在证据不充分的情况下能够更快速、正确地判断入侵事件，从而进一步提高检测的效率。
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