| ID | 原文 | 译文 |
| 5584 | 为了降低运算量,利用目标信号频率相对于整体频域是稀疏的特性,采用基于SFT搜索的方法通过梯度下降的方式避免滤波器的遍历搜索。 | In order to reduce the computational complexity, use of the target signal frequency relative to the overall characteristics of frequency domain is sparse, based on the SFT by gradient descent search method avoid ergodic search filter. |
| 5585 | 仿真实验验证了所提方法的有效性。 | Simulation experiments verify the effectiveness of the proposed method. |
| 5586 | 针对传统故障模式及影响分析(failure mode and effect analysis,FMEA)中主观性较强以及权重分配不够合理的问题,提出基于模糊理论与Dempster-Shafer (D-S)证据理论的FMEA方法。 | For traditional failure mode and effect analysis (failure mode and effect analysis, FMEA) in strong subjectivity and unreasonable weights allocation problem, put forward based on fuzzy theory and the Dempster - Shafer (D S) evidence theory method of FMEA. |
| 5587 | 首先,参考软件FMEA方法,将故障被检测度引入到硬件FMEA方法中,并应用模糊理论建立模糊评定等级及对应模糊数。 | FMEA method, first of all, the reference software will be introduced to the degree of fault is detected hardware FMEA method, and applies the fuzzy theory to establish fuzzy rating and the corresponding fuzzy Numbers. |
| 5588 | 其次,提出基于D-S证据理论的专家赋权法合理分配权重。 | Secondly, based on D - S evidence theory expert empowerment method reasonable weight distribution. |
| 5589 | 最后,基于风险优先数(risk priority number,RPN)得出各故障模式的风险排序。 | Finally, based on the risk priority number (risk priority number, RPN) it is concluded that the risk of each fault mode. |
| 5590 | 案例分析表明该方法可以根据评估偏差量来科学地分配权重,使得评估结果更合理、RPN值更准确、故障模式风险排序更客观。 | Case analysis show that this method can scientifically according to the evaluation of deviation value distribution of weight, make evaluation results more reasonable, RPN value, risk of failure mode is more objective and more accurate. |
| 5591 | 该方法能够满足实际需要,在工程实践中值得推广应用。 | This method can satisfy the actual needs, worthy of popularization and application in engineering practice. |
| 5592 | 复杂网络关键节点与关键连边在网络中均起着十分重要的作用,目前的识别方法往往无法做到同时识别,并且识别指标角度较为单一。 | Complex network key nodes with critical edge plays a very important role in network, the recognition method often can't identify at the same time, and identify target Angle is relatively single. |
| 5593 | 为解决上述问题,提出一种基于最小连通支配集(minimum connected dominating set,MCDS)的复杂网络关键节点与连边识别方法,通过使用免疫粒子群(immune particle swarm optimization,IPSO)算法寻找网络最小连通支配集,构建核心骨干网,实现对复杂网络关键节点与连边的同时识别。 | In order to solve the above problems, and puts forward a kind of based on minimum connected dominating set (minimum connected dominating set, MCDS) a complex network of key node and edge recognition method, by using the immune particle swarm (immune particle swarm optimization, IPSO) algorithm for minimum connected dominating set network, build core backbone network, realizes the key nodes of complex networks and at the same time, on the edge of the identification. |