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- The influences of experiment design by steps on RBF network metamodel were also measured by numerical tests.The training sampling set of RBF network wss decided upon by uniform design. 最后采用径向基神经网络替代模型,以均匀试验设计为例,检验分步试验优化设计方法的有效性。
- Data from mechanical models computing and fields sampling are gathered to generate training samples with good orthogonality and wide ranges, which can improve the generality and reliability of models. 将机理模型计算数据与现场采集数据相结合,获得正交性和完备性较好的训练样本数据,增强模型的外推能力和可信度。
- In this method, rule intensity is defined according to the number of misclassified training samples. 该算法根据误分类训练样本的数量定义规则强度。
- SVM is used to classify, which weakly depends on the quantity and quanlity of training samples. 在分类器设计方面,选用了对样本数量和质量依赖性小的支持向量机。
- Besides that, we adopted a bootstrapping method during network's training, successfully solving the deficiency of non-face training samples. 而改进后的BP网络缩短了学习时间,提高了学习效率,并在一定程度上避免了学习中的局部极小问题。
- To classify the collectivity, uaually a training sample is needed.The classification and statistical indexes of the training sample are known. 为了对总体分类,一般应该有训练样本,它的分类和统计指标都是已知的。
- To address the quality problem of training samples, this article uses sample weightiness analysis to select training samples. 为了解决训练样本质量过差的问题,本文通过重要性分析方法进行训练文本选择。
- The discrimination model is established from the training samples using BP algorithm,and then the samples is distinguished from the well-trained. 利用BP算法对训练样本进行学习,确定判别模型,根据已训练好的神经网络对样本进行判别。
- In the training of the neural network model (NNM) of the plant and the neural network controller (NNC), training samples are got from the state function of the plant. 在训练实现对象模型的网络和实现控制器的网络时,由状态方程产生训练样本。
- An automatic text categorization mechanism based on CBR was presented,the training sample library was converted to the case library and the document was classified by KNN. 文中提出了一种基于CBR的文本自动分类方法,先用聚类方法把训练样本库转换为范例库,然后用KNN思想分类。
- The method divides theoriginal data into two parts in term of "close" degree between the original sample and forecast sample: one is initial sample, the other is training sample. 本方法对原有的样品数据根据与待预测样品的关系的“密切”程度分为两个部分,一部分是初始样品,一部分是训练样品。
- The denominator of generally neural network output often tends to be zero,leading to infinite loop when training sample data.The reliability of results is debased. 常规神经网络在当训练样本时分母项易趋于0,导致运算进入死循环,降低了结果的可信度。
- In this paper the training samples, training method of neural network and the way combined with ADRC is analyzed, and the valuable conclusion is obtained. 文中对神经网络的训练样本、方法及其与自抗扰控制器结合的方式进行了分析和讨论,并得出了有益的结论;
- Experiment result shows that as reserving typical samples and reducing training samples, the generalization performance and training efficient of the classifier are guaranteed. 仿真结果证实,由于保留了典型样本,减少了训练样本数量,从而保证了分类器的性能且训练效率较高。
- To boost the recognition performance in this one training sample application scenario, we extract context information as another cue for recognizing people. 为了在这单一训练样本的情况下提高人脸分类的识别性能,我们亦由输入的照片集中,萃取出前后文讯息,来做为分类判断的另一种线索。
- Hard training will fit them to run long distances. 严格的训练将使他们能跑长距离。
- The algorithm can obtain the better classifiers by using less training samples,so it leads to more generalization and less training samples than the other learning models. 该算法能用较少的训练样本获得更佳的分类器,因此它的推广能力较好,且对训练要求的样本数也大大下降。
- She earned her place in the team by training hard. 她由于刻苦训练而在队里取得了地位。
- In order to prevent causing network incorrectly incline with one of fault type after training, the number of training samples for every fault should be allocated averagely. 为了防止人为的造成训练后的网络过多的倾向于某一故障类型,各故障类型的训练样本数量不应相差太多。
- Its weighted training error and scaling factor cm is computed (step 3b).The weights are increased for training samples, which have been misclassified (step 3c). 计算错误率和换算系数cm(step 3b).;被错分的样本的权重会增加。