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artificial neural network (ann)中文是什么意思

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  • As the most typical cognitive model of artificial neural networks ( ann ) , traditional adaptive resonance theory ( art ) still can not simulate the human ' s multi - fold ambiguous perception for lacking of a controllable mechanism to adjust the system ' s vigilance parameter
    Art是神经网络认知模型中最典型的代表,但还没有一种控制机制可以对该模型的注意参数进行调节,因而不能仿真人的认知中的多义感知的振荡现象。
  • Artificial neural network ( ann ) is one kind of ai method which is stood up by imitating person ' s brain nerve delivering information . it is one kind of distributed parallel processing system , the acquired results save in the matrix with weight values distributed
    人工神经网络是一种模拟人脑脑神经传递信息的方式而建立起来的一种人工智能的方法,它是一种分布式的并行处理系统,其处理结果以权值形式分布存储在矩阵中。
  • There are some limitations for solving these problems by the expert system ( es ) based on the symbol study and inference . therefore , some numerical value analysis methods are researched . for example artificial neural network ( ann ) and fuzzy recognition technique ( frt )
    基于符号学习和推理的专家系统在解决这个问题上的某些局限性,使基于数值计算的诊断方法,如人工神经网络和模糊识别等,成为智能故障诊断研究的新课题。
  • The application of artificial neural networks ( ann ) to automatic speech recognition ( asr ) is investigated in this thesis . the recognition of speaker - independent and isolated words is focused and three types of ann model are presented . the related algorithms and programs are developed
    本文基于自动语音识别( asr )的原理和过程,结合人工神经网络( ann )的建模理论及特点,主要研究了人工神经网络在自动语音识别中的应用问题。
  • At the end of the thesis , intellectual capital is further measured by artificial neural networks ( ann ) , moreover the relation between result of non - financial measurement and the value of intellectual capital is researched . this model is then applied to a knowledge - based company
    最后,本文运用建立起来的测量模型对一家典型的知识型企业加以实际测量,实践结果表明,该测量方法是切实可行的,并对企业的战略管理具有积极的指导意义。
  • Those are classical time series analysis , markov model , grey predicting , artificial neural network ( ann ) . in terms of indemnifying model coefficients , the author develops two ga versions embedded the two bit genetic operators , for evaluating classical time series models and the weights of ann
    针对模型参数识别问题,笔者又提出了两种嵌入了基本位遗传操作算子的ga新策略,分别用于识别经典时序模型的参数和优化人工神经网络模型(简称ann )的权重。
  • In this work the artificial neural network ( ann ) and particle transport theory were studied , considering the tgs characteristics and the two new reconstruction techniques , ann and monte carlo statistical iteration tgs transmission image reconstruction method , were proposed
    本文根据tgs上述特点和要求,分别从神经网络和mc模拟两种不同的技术,提出了两种tgs透射测量图像重建的新算法:神经网络tgs透射测量图像重建算法和mc统计迭代透射测量图像重建算法。
  • In this paper , the electromagnetic band gap ( ebg ) structure is modeled by using the artificial neural network ( ann ) , and the ann is trained with the converse method . as the ann is used in the design of ebg structure , the design time is shortened and the design cost reduced . the ann results are in good agreement with the calculated results , which shows that the approach used in this paper is valid
    文章采用人工神经网络对电磁带隙结构进行建模,并结合逆向方法训练网络;神经网络用于电磁带隙结构的设计,具有缩短设计时间、降低设计成本的优点;通过文中实例可以看出,人工神经网络设计的结果与数值仿真的结果吻合良好,显示出该方法的有效性。
  • To perform more efficiently , a mixed expert system ( mes ) based method is proposed in our research , which combines artificial neural network ( ann ) technique with traditional expert system ( es ) to deal with the qualitative factors of various aspects in enterprise credit assessment . the focus of this work is concentrated at the ann module of that method
    因为神经网络适合处理定量的数据,而专家系统适合处理处理定性的数据,本课题我们用神经网络和专家系统分别对企业定量、定性两方面信用风险的成因进行研究,有机、科学地结合两者的的优点,最终得到企业信用等级的综合评价。
  • Based on the theory and procedure of the automatic speech recognition ( asr ) , and combined the theory and characteristics of the artificial neural networks ( ann ) , the research in this paper is oriented on the theory and application of the mixed model ? hmmnn , which is formed by the combination of the hidden markov model ( hmm ) and the self - organized neural networks ( sonn ) , and the related algorithms and model are developed
    本文基于自动语音识别( asr )的原理和过程,结合人工神经网络( ann )的建模理论及特点,主要研究了隐含马尔可夫模型( hmm )与自组织神经网络( sonn )相结合的混合模型hmmnn的原理及在语音识别中的应用,分析构造了相应的语音识别模型与算法。
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