ID 原文 译文
25285 然后使用训练数据集合对贝叶斯网络进行结构学习学得贝叶斯网络结构，以及参数学习学得与贝叶斯网络结构匹配的条件概率表; Then the training data set is used to learn the structure of the Bayesian network and the conditional probability table matching the structure of the Bayesian network.
25286 最后加入附加信息计算出每种降水粒子类先验概率，与贝叶斯网络结构和条件概率表共同组成贝叶斯网络分类器。 At last, additional information is added to calculate the prior probability of each precipitation particle class, and the Bayesian network classifier is composed of Bayesian network structure and conditional probability table．
25287 训练好的贝叶斯网络分类器根据最大后验概率准则完成对测试数据的降水粒子分类，与模糊逻辑算法对比评价结果。 The trained Bayesian network classifier classifies the precipitation particles according to the maximum posterior probability criterion and compares the evaluation results with the fuzzy logic algorithm．
25288 实验证明:该方法能有效区分不同的降水粒子得到准确的降水粒子分类结果。 Experiments show that this method can effectively distinguish different precipitation particles．
25289 针对传统多目标威胁评估方法通常是二支决策，只能得到目标威胁排序，需要主观地划定威胁等级与选择作战目标数，不适应于复杂动态任务环境的问题，提出直觉模糊信息下基于 VIKOＲ 和三支决策的多目标威胁评估方法。 The traditional multi-target threat assessment methods are usually two-way decisions，can only obtain thethreat ranking of targets，and need to subjectively determine the threat level and select the number of combat targets，which isnot suitable for the complex dynamic mission environment. This paper proposes a multi-target threat assessment method based on VIKOＲ and three-way decisions under intuitionistic fuzzy information.
25290 首先，对动态直觉模糊威胁评估信息进行集结并求取属性权重; Firstly, the dynamic intuitionistic fuzzy threat information is aggregated and attribute weights are obtained．
25291 然后，通过 VIKOＲ 方法求取目标决策所需的条件概率; Then, the conditional probability of targets for decision making is obtained by VIKOＲ method．
25292 最后，通过评估信息构造各属性下目标的损失函数矩阵，集结得到目标的综合损失函数矩阵，计算综合阈值，得到决策规则。 Finally, the loss function matrices of targets under each attribute are constructed by attribute information, the comprehensive loss function matrix is obtained after aggregation and the comprehensive thresholds and decision rules are obtained．
25293 算例分析表明，所提方法能够有效地处理动态不确定目标态势信息，将传统方法的二支排序结果转变为三支分类结果;可以依据目标态势信息客观地选取作战目标。 The case studies show that the proposed method can effectively deal with the dynamic uncertain situation information, transform the ranking results of two-way decisions into classification results of three-way decisions, and can objectively select the combat targets via situation information．
25294 软件定义网络作为未来网络架构的发展方向，通过分离数据平面与控制平面高效设定路由方案。 As the development direction of future network architectures, Software Defined Networks can efficiently setrouting schemes by separating the data plane and the control plane．