ID 原文 译文
45826 然后，按照优化排序原则从 2 个列表中选取交换机和控制器实施双向匹配，并通过模拟退火算法优化匹配关系，实现分布式网络中多控制器的动态部署。 According to the principle of optimal queuing, switches and controllers were selected from two match lists for implementing bidirectional matching, and the relationship of matching with the help of simulated annealing algorithm was optimized, which achieved dynamic deployment for multi-controller in distributed network.
45827 仿真结果表明，与现有的方法相比，该算法能够合理配属交换机和控制器之间的连接关系，有效降低流请求排队时延， Results show that, compared with the existing approaches, this algorithm can match the connections between switches and controllers reasonably, and reduce the queue delay of flow request effectively.
45828 同时控制器负载均衡率至少提高了 17.9%。 Moreover, and the controller load balancing rate has increased by 17.9% at least.
45829 针对传统基于信任网络的服务推荐算法中信任关系稀疏以及通过 QoS 预测值排序得到的服务推荐列表不一定最符合用户偏好等问题，提出基于信任扩展和列表级排序学习的服务推荐方法（TELSR）。 In view of the problem of trust relationship in traditional trust-based service recommendation algorithm, andthe inaccuracy of service recommendation list obtained by sorting the predicted QoS, a trust expansion and list wise learning-to-rank based service recommendation method (TELSR) was proposed.
45830 在分析服务排序位置信息的重要性后给出概率型用户相似度计算方法，进一步提高相似度计算的准确性； The probabilistic user similarity computation method was proposed after analyzing the importance of service sorting information, in order to further improve the accuracy of similarity computation.
45831 利用信任扩展模型解决用户信任关系稀疏性问题，并结合用户相似度给出可信邻居集合构建方法； The trust expansion model was presented to solve the sparseness of trust relationship,and then the trusted neighbor set construction algorithm was proposed by combining with the user similarity.
45832 基于可信邻居集合，利用列表级排序学习方法训练出最优排序模型。 Based on the trusted neighbor set, the list wise learning-to-rank algorithm was proposed to train an optimal ranking model.
45833 仿真实验表明，与已有算法相比，TELSR 在具有较高推荐精度的同时，还可有效抵抗恶意用户的攻击。 Simulation experiments show that TELSR not only has high recommendation accuracy, but also can resist attacks from malicious users.
45834 针对 K 个用户 MIMO 干扰信道（IC），研究基于分布式空时干扰对齐（DSTIA）的信道可达自由度。 In the context of K-user MIMO interference channel (IC), achievable degrees of freedom (DoF) were investigated with distributed space-time interference alignment (DSTIA).
45835 利用分布式当前和过期发射端信道状态信息（CSIT）设计预编码，分别给出 MISO 系统可达自由度关于 CSI 反馈时延和反馈频率的折中域； By precoding with distributed current and outdated channel state information at the transmitters (CSIT), new tradeoff regions between achievable DoF and CSI feedback delay/frequency were achieved for MISO system.