基于ART2的网络入侵检测算法是在自适应共振理论的基础上改进而来的。
The algorithm of network intrusion detection which based on ART2is an improvement grounded on automat-ic adaptive theory.
然后利用ART （自适应共振理论）网络对残差进行自动分类，不需要故障的先验知识。
Second, ART(Adaptive Resonance Theory)is adopted to classify the residuals automatically, no apriori knowledge is required.
目的基于自适应共振理论，提出一种基于ART2神经网络的结构损伤识别方法，以实现结构损伤识别的自主学习。
An ART2 neural network based on adaptive resonance theory is put forward in this work to identify the damage of the structures and to realize the on-line self-study of the network.
利用人工神经网络法中的自适应共振理论优选钻头 ，将定性、定量优选因素作为输入层神经元 ，形成一种综合性选型方法 。
The new network model is formed by incorporating the two concepts of fuzzy set theory, closeness and closest principles, with adaptive resonance theory (ART).
利用人工神经网络法中的自适应共振理论优选钻头 ，将定性、定量优选因素作为输入层神经元 ，形成一种综合性选型方法 。
The new network model is formed by incorporating the two concepts of fuzzy set theory, closeness and closest principles, with adaptive resonance theory (ART).
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