• Based on this, the article improves classical ART2 network by taking amplitude as character component.

    文章针对此不足,将样本的幅度作为样本特征分量的办法,对传统的ART2网络进行了改进。

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  • A model for dirty data identification and justification is put forward based on the modified ART2 network.

    文中提出了基于改进ART2网络的脏数据辨识与调整模型。

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  • An ART2-based dynamic risk management model is proposed by using of clustering technique and neural network knowledge.

    结合聚类技术和ART2神经网络技术提出一个基于ART2神经网络的动态风险管理模型。

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  • By analyzing ART2 neural network clustering algorithm, an improved ART2 neural network clustering algorithm was proposed.

    分析了现有ART2网络存在的问题,提出了一种改进的ART2算法。

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  • The integrated ANN consists of fuzzy ART2 and BP network has ability of finding new fault type, accurate diagnostic reasoning and locating fault.

    基于模糊ART神经网络及BP神经网络构建的集成神经网络更进一步具有发现新故障的能力,且能够对故障引发部位实现精确诊断和定位。

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  • The character, mechanism of ART2 and the method of fusing data got by multi-sensors are analyzed, at the same time the step of achieving the system is also got.

    文中介绍了ART2网络的特点、工作原理和对通过多路传感器所获得的实验数据进行融合的方法及数据处理的步骤,并给出了具体的实现过程;

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  • Although ART2 neural network can well realize the clustering of dynamic samples, the problems arising from ART2 neural network itself restricted its application.

    ART2神经网络虽能很好地实现这类动态数据的聚类,但ART2网络本身存在的问题又限制了它在这方面的应用。

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  • The AE signals of tool conditions were decomposed using a recursive wavelet from which the features are extracted and delivered to an ART2 network for fault recognition.

    对刀具AE信号进行递归小波分解,提取特征并应用ART2网络识别刀具状态。

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  • The AE signals of tool conditions are decomposed using a recursive wavelet from which the features are extracted and delivered to an improved ART2 network for fault recognition.

    对刀具ae信号进行递归小波分解,提取特征并应用于改进的ART2网络识别刀具状态。

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  • Whereas, an improved ART2 neural network clustering algorithm is proposed to realize the clustering of dynamic samples, and the simulation results are given out at the same time.

    鉴于此,本文又提出了一种改进的ART2网络学习算法来实现动态样本的聚类,同时给出了该方法的实验仿真结果。

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  • On the other hand, the watchful limit and the switching control for running state in the network were introduced, which combined the ART2 network's unsupervised training ability.

    另一方面结合ART2神经网络无师学习的特点,引入了网络警戒门限和运行状态切换控制。

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  • 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。

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  • 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。

    youdao

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