The teaching model based on the schema theory stresses the importance of the prior knowledge in reading and writing.
基于图式理论的教学模式强调原有知识在阅读和理解语篇方面的重要性。
Simulation results show that the presented method can accurately construct the inverse dynamic model of the continuous nonlinear system even without prior knowledge about the controlled plant.
仿真结果表明，在没有被控对象先验知识的情况下，利用该方法能准确地建立连续非线性系统的逆模型。
The classification based on cloud model always USES cloud transform and Pan-Concept-Tree, it brings on inconsistency between the result and prior knowledge.
基于云模型的分类算法多采用云变换和泛概念树方法，存在分类结果与先验知识不一致的问题。
The method relies on active perturbation to the system to obtain prior knowledge for building the model, and then constructs the dependency model based on the methods of building Bayesian networks.
这个方法通过对系统进行主动干扰来获得建模的先验知识，然后基于贝叶斯网络构造方法，对分布式应用的组件间关系建立依赖性模型。
The kernel estimation method analyzes the data distribution by not using the prior knowledge of data distribution. This method avoids the impaction of model and parameters estimation.
核密度估计方法从数据样本本身出发研究数据分布特征，不利用有关数据分布的先验知识，避免了模型估计和参数估计的主观影响。
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。
In this paper, we research the CamShift tracker in detail and then proposed to build multiple color-distribution-model for the target accordng to prior knowledge of the objects appearance.
本文在对连续自适应均值漂移算法深入分析的基础上，提出利用目标外观信息的先验知识，对其建立多个颜色分布模型。
Among various data mining technologies, Evolution Computing has been widely applied in complex problem handling because it requires little field knowledge and no prior model.
进化计算模型不需要太多领域知识和建立先验模型，在处理复杂的数据挖掘问题中得到了广泛的青睐。
However, the parameter model based PSD estimation is used with the assumption that the model order is determined as low as possible through prior knowledge.
而功率谱估计中基于参数模型的方法得到广泛应用，但建模时通常只能根据经验选择一个固定较低的阶数。
The query model first calculates the prior knowledge of the feature vectors and then dynamically chooses the feature vector with the best description.
该 算法利用查询模型计算各种特征向量的先验知识，然后动态地选择描述能力较强的特征向量计算模型之间的相似度距离。
The query model first calculates the prior knowledge of the feature vectors and then dynamically chooses the feature vector with the best description.
该 算法利用查询模型计算各种特征向量的先验知识，然后动态地选择描述能力较强的特征向量计算模型之间的相似度距离。
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