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连续数据的英文

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"连续数据"怎么读用"连续数据"造句

英文翻译手机手机版

  • continuous data

例句与用法

  • 113 run : a number of consecutive data elements represented in the decoding process
    行程:在解码过程中连续数据元素出现的个数。
  • Concatenated data set
    连续数据
  • A dynamic routing algorithm based on application rules and probability in wireless sensor networks was proposed
    针对连续数据分发型传感器网络,提出了一种基于应用规则和概率的动态路由算法rpdr 。
  • An abstract data type is just a contiguous chunk of data associated with an address point to it , cast it about , pick it apart , and move on swiftly
    抽象数据类型只是与地址相关联的连续数据块指向它,对它进行强制转换,对它进行解析,然后快速向前推进。
  • This method is best used for normal distribution curves , but does not work well if the distribution includes a large number of values that occur in a narrow group in the continuous data
    此方法最适用于正常分布曲线,但如果分布包含的值数量很大,并且这些值在连续数据的窄组中,则此方法的使用效果不是很好。
  • The analysis and design class diagram are given . the sequence indication stochastic simulation algorithm based on indicator kriging is realized . the algorithm applies to discrete and continuous variable has no restrict to data distribution
    系统给出了沉积相随机建模的分析类图和设计类图,实现了基于指示克里金估计的序贯指示随机模拟算法,该算法对离散数据和连续数据都适用,不要求数据的分布特征,可以较好的模拟相特征。
  • Firstly , influence factors of generalization of neural network are presented in this thesis , in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability , a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes , training epochs , initial weights , and so on ; secondly , through establishing integrating neural network and introducing data fusion technique , the integrality and precision of acquired knowledge is greatly improved . then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement , knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system , by completing missing value data and eliminating unnecessary attributes , discretization of continuous attribute , reducing redundancy , extracting rules in this thesis . finally , rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge , in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement , and rnn can improve the speed and quality of knowledge acquirement greatly
    本文首先讨论了影响神经网络的泛化能力的因素,提出了一种新的结构自适应神经网络学习算法,在新方法中,采用了遗传算法对神经网络的结构参数(隐层节点数、训练精度、初始权值)进行优化,大大提高了神经网络的泛化能力和知识动态获取自适应能力;其次,构造集成神经网络,引入数据融合算法,实现了基于集成神经网络的融合诊断,有效地提高了知识获取的全面性、完善性及精度;然后,针对知识获取过程中所存在的不确定性、不完备性等问题,探讨了运用粗糙集理论的知识获取方法,通过缺损数据补齐、连续数据的离散、冲突消除、冗余信息约简、知识规则抽取等一系列的算法实现了智能诊断的知识规则获取;最后,将粗糙集理论与神经网络相结合,研究了粗糙集-神经网络的知识获取方法。
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