This paper presents a new adaptive phase selector with an adaptive resonance theory (ART) based neural network.
提出一种新的基于自谐振神经网络结构的自适应故障选相元件。
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.
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。
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).
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 。
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