The typical computation model of training effectiveness of training plane has limitation in selection of flight parameters as well as insufficient attention to avionics and control system.
典型的教练机训练效能计算模型对飞机的航空电子系统、操纵系统考虑不足，对飞行参数选择有局限性。
Parameters of the model about testing image and about training images are compared to classify the testing image.
通过比较被测试图像的模型参数和训练集图像的模型参数确定被测试图像的类别。
After introducing the structure of the new model, we give the estimation formulas for the parameters of the new model and the algorithms for training and recognition.
本文在给出新模型的框架后，推导了模型参数的估值公式，并给出了模型的训练和识别算法。
The training of the novel model utilizes the maximum likelihood criterion and an effective EM algorithms to adjust model parameters is developed.
新模型的训练采用最大似然准则，并改进了EM算法来调整模型参数。
The learning of Bayesian Networks is an important tache, which combines training data with prior knowledge and model evaluation to acquire the structure hidden in data and parameters.
贝叶斯网络的学习是数据挖掘中非常重要的一个环节，是将先验知识和模型评价融入训练数据，获得数据中隐藏的拓扑结构和参数的过程。
The intelligent simulation model of blast furnace cast steel stave based on correction factor of parameters obtained by training the samples of test data of cast steel stave.
通过训练冷却壁热态试验数据样本，得出了基于参数修正因子的高炉冷却壁的智能仿真模型。
So you will need a training dataset without outliers, a validation dataset with outliers for choosing parameters, and a final test dataset with classifiers to see whether your model generalizes.
所以你需要一个训练集没有异常值，异常值与参数选择的验证数据集，和一个最终的测试数据集的分类看你的模型概括。
The traditional training methods of Gaussian Mixture Model(GMM) are sensitive to the initial model parameters, which often leads to a local optimal parameter in practice.
为了解决传统高斯混合模型（GMM）对初值敏感，在实际训练中极易得到局部最优参数的问题，提出了一种采用微粒群算法优化GMM参数的新方法。
Four typical discriminative training criterions and some updating methods of acoustic model parameters are introduced, then, they are defined in a unified framework.
再经过对各种区分性训练准则的目标函数和参数更新算法进行推导和比较，将它们统一地纳入到一套训练框架体系之中。
Four typical discriminative training criterions and some updating methods of acoustic model parameters are introduced, then, they are defined in a unified framework.
再经过对各种区分性训练准则的目标函数和参数更新算法进行推导和比较，将它们统一地纳入到一套训练框架体系之中。
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