1) ART1
ART1自适应谐振网
2) Adaptive resonance theory(ART)
自适应谐振网络
3) adaptive resonance
自适应谐振
1.
To improve clustering reliability of adaptive resonance theory(ART) under situation of small sample set,an optimum algorithm of training set of ART2 neural network based on genetic algorithm was presented in the paper.
为了提高小样本集情况下自适应谐振(ART)神经网络聚类的可靠性,提出了基于遗传算法的ART2神经网络训练集优化算法,克服了ART1神经网络编码的稳定性尚未完全解决和只能接受二进制模式的缺陷。
4) adaptive resonance neural networks
自适应谐振神经网络
5) adaptive resonance theory
自适应谐振理论
1.
For learning document classification on line,the paper gives the semi-supervised learning fuzzy ART model (SLFART) based on adaptive resonance theory and the model s algorithm.
为了对在线学习文档进行分类,本文根据自适应谐振理论给出了一个半监督学习模糊ART模型(SLFART)及其算法。
2.
Through analyzing adaptive resonance theory,a dynamic classification algorithm based on associative and competitive learning is provided.
为了使分类方法适合网络入侵检测系统在线、实时的特点,根据自适应谐振理论提出了基于联想和竞争学习的动态分类算法。
6) ART
[英][ɑ:t] [美][ɑrt]
自适应谐振理论
1.
A semi-supervised learning system was proposed based on ART(adaptive resonance theory).
根据自适应谐振理论提出了半监督学习自适应谐振理论系统。
2.
In this paper,an approach is presented to recognize vehicle characters based on adaptive neural network constructed by ART,combined with the neural network s adaptive feature,which effectively improves recognition rate.
结合神经网自适应的特点 ,本文利用基于自适应谐振理论 (AdaptiveResonanceTheory ,ART)构成的自组织神经网络进行字符识别 ,给出了算法和实验结
3.
Through inspection of the relevant papers found that the adaptive resonance theory(ART) has been developed to avoid the stability-plasticity dilemma in competitive networks learning.
通过对相关文献的查阅后发现,由于自适应谐振理论(Adaptive ResonanceTheory,ART)网络较好地解决了传统的神经网络中稳定性与可塑性之间的矛盾,即在ART网络的学习过程中,网络既可以稳定地学习新知识,也可以对已学习的新知识做出很好的吸收处理的优点,使得其在地震预报领域里被多个学者专家所采用。
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1.徒自，徒然。
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