learning algorithm的例句大全

compared with relearning vocabulary, this transfer learning algorithm makes use of learned knowledge effectively, which can gain good performance especially in the situation when there are a few images in a novel category.

与重新学习视觉词典的分类算法相比，这种迁移算法有效地利用了已有知识，在新类别图像的训练样本较少的情况下，也能获得较好的分类效果。

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The existing distributed machine learning algorithm library, Mahout, offers some classic classification algorithm, such as Bayes and decision trees.

现有的分布式机器学习算法库Mahout，提供了一些经典的分类挖掘算法，如贝叶斯、决策树等。

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Reinforcement learning algorithm based on average cost optimization for each stage

基于每阶段平均费用最优的激励学习算法

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presents the mathematical expressions of adding new learning sample and adding new redial basis function of relearning algorithm, studies how to get the new learning sample.

详细给出了径向基函数神经网络再学习算法中增加新训练样本和增加新基函数的数学公式，同时对如何获取新的训练样本进行了研究。

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Structure Learning Algorithm for DBN Transition Networks Based on Ant Colony Optimization

基于蚁群优化的DBN转移网络结构学习算法

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Graph-based semi-supervised learning algorithm is drawing lots of attention in recent years due its some internal characteristics.

半监督学习中的基于图的算法由于自身的一些特殊性质，越来越引起人们的关注。

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Managing Buffer Appropriately with the Back Propagation Learning Algorithm

利用反向传播算法合理分配缓冲区

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Semi-supervised Active DBN Learning Algorithm Based on EM and Classification Loss

一种基于EM和分类损失的半监督主动DBN学习算法

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The incremental learning algorithm in hybrid learning model HLM

混合型学习模型HLM中的增量学习算法

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Based on the delay time phase reconstruction of the chaotic dynamical system and the nonlinear characterization of the neural networks, the prediction of factual EEG signals were investigated by using the radial basis function neural networks with the adaptive projective learning algorithm.

基于混沌动力学系统相空间的延迟坐标重构及人工神经网络的非线性特性。研究了采用基于自适应投影学习算法的径向基函数网络对实测的EEG信号进行预测。

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Paper accounts the concept, background and application scope of data driven, the iterative learning algorithm, and verifies the convergence of the control method.

本文详细叙述了数据驱动的概念、背景及应用范围，并阐述了迭代学习控制方法，进一步验证了该控制方法的收敛性。

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The algorithm speeds up network study train, compared with the Real-time Recurrent Learning algorithm consumedly, and increases the accuracy of prediction.

与已有的实时循环学习算法相比，极大的提高了网络学习训练的速度，并且提高了预测的精度。

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In this paper, we first analyze the deficiencies of traditional fuzzy neural networks and improve the learning algorithm. The Layer-Proceeding BP Neural Networks ( LPBPNN) is given based on the hierarchical error and the learning rate which can cooperatively adjust.

本文首先分析了传统的模糊神经网络存在的缺陷，改进了学习算法，提出了将误差与学习率分层，协同调整的层递式BP神经网络。

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The learning algorithm is given, and the effectiveness of the model and algorithm is proved by tertiary oil recovery process simulation of oil reservoir development.

文中给出了学习算法，并以油藏开发三次采油过程模拟为例验证了模型和算法的有效性。

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Based on the fundamental rules of human brain's analyzing and reasoning in clustering, this paper proposes a learning algorithm of neural networks of fuzzy hypersphere barycenter Clustering.

基于人的大脑进行聚类分析所遵循的基本原则，提出了一种模糊超球质心聚类神经网络学习算法。

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Study on Adaptive Fuzzy Control System Based on Gradient Descent Learning Algorithm

基于梯度下降法的自适应模糊控制系统研究

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Improving the SA Learning Algorithm

BP网络局部学习速率自适应SA算法的改进

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A weighted class incremental learning algorithm is presented, which improves the CIL algorithm. The algorithm adds the weighs of class to training samples.

提出了一种加权类增量学习算法，该算法是对CIL算法的改进，通过加入类权值，解决了因两类训练样本不平衡而造成的小类别分类精度较低的问题。

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The advantages and weaknesses of each type time delay compensation algorithm are analyzed, leading to the iterative learning algorithm. Thirdly, the effect of the network time delay to the linear system is analyzed and the time delay composition model is built.

分析每类时滞补偿算法的优点和不足，并引出迭代学习算法。再次，分析网络时滞对线性系统的影响，对时滞进行分析和建模。

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furthermore, in order to overcome the disadvantage of the centralized computing of rpe learning algorithm, a parallel structure algorithm is derived.

进一步地，为了克服RPE算法集中运算的不足，设计完整的并行结构算法。

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