ID 原文 译文
25565 其次，依据度值和传输能力构建重要度传输矩阵，综合节点局部重要性和全局属性指标评价节点的重要性。 Secondly, the node degree and transmission capacity are used to construct the importance transmission matrix, and the local importance and global attribute index of the node are integrated to evaluate the importance of the node．
25566 最后，对“ARPA”网络和四个真实网络进行破坏性仿真分析，结果本文方法表明对网络造成更大的破坏，证明了该方法的有效性和可靠性。 Finally, destructive simulation analysis on the "ARPA" network and four real networks show that this method causes more damage to the network, which proves the method's effectiveness and reliability．
25567 GNSS(Global Navigation Satellite System)欺骗干扰装备，是“导航战”重要组成，对其效能的有效评估决定了目标任务的成功。 GNSS (Global Navigation Satellite System) spoofing equipment is the important components of "Navigation war". The valid evaluation of its effectiveness determines the success of the target task．
25568 但目前存在影响因素的模糊性和不确定性大、因素间影响关系的传递性弱、评估方法适用性差、评估效率低等难点问题。 However, there are still many difficult issues, such as the great ambiguity and uncertainty of influencing factors, the weak transitivity of influencing relations between factors, the poor applicability of assessment methods and the low evaluation efficiency．
25569 针对这些问题，本文提出一种基于灰色关联分析和模糊综合评判的评估方法。 To deal with these problems, an evaluation method based on grey relational analysis and fuzzy comprehensive assessment is proposed．
25570 在指标体系搭建完成的基础上，利用层次分析法确定指标权重，并通过纵向计算灰色关联度，得到最优方案; Firstly, the optimal scheme is obtained by calculating grey relational degree longitudinally.
25571 再通过模糊综合评判，得到最优方案的评估结果; Secondly, the evaluation results of the optimal scheme are obtained by using fuzzy comprehensive assessment．
25572 最后通过横向计算灰色关联度，来选取与评估结果关联度高的指标。 Finally, the indexes highly correlated with the evaluation results are selected based on calculating gray relational degree horizontally．
25573 实验证明，本文提出的方法解决了评估存在的难点问题，达到有效评估的目的。 The test results show that these difficult problems are solved by the method proposed in this paper．
25574 宽带压缩频谱检测存在信号稀疏度未知和次用户检测开销过大的问题。 Wideband compressed spectrum sensing has the problems of unknown signal sparsity and high overhead of secondary users sensing．