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中文摘要：
将自适应小波网络模型与免疫进化算法有机结合，提出基于免疫自适应小波网络的入侵检测模型及学习算法．该模型不仅减少经典神经网络在确定参数和结构时的盲目性，而且减轻对参数初始化敏感的现象．仿真对比实验结果表明，用本文算法获得的检测率比神经网络、小波网络、免疫进化的方法都要高，收敛速度更快，同时可通过控制门限值来约束和平衡漏报率和误报率之间的关系．
英文摘要：
An adaptive immune wavelet network based intrusion detection model and the related algorithm are proposed by combining an adaptive wavelet network model with immune algorithm in this paper. The model not only avoids blindness of determing parameters and construction of neural network , but also alleviates sensitivity to initialization . The experimental results show detection rate acquired in this algorithm is higher than that in other algorithms and its convergency speed is higher than others＇. Moreover, the relationship between False Negatives and False Positives can be restricted and balanced by adjusting a threshold value.
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