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identification相关的网络例句

查询词典 identification

与 identification 相关的网络例句 [注:此内容来源于网络,仅供参考]

The proposed network topology identification algorithm in this paper requires no support from internal nodes, it infer network internal performance and topology by using end-to-end measurement.

提出的网络拓扑推断算法不需要网络内部节点的协作,通过端到端测量推断网络内部的性能特征和拓扑结构。

With the fact that there are some topology vector s that vary with different formula in each circuit topology, another identification way can be carried out by selecting and measuring the best.

另一方面,基于电路的拓扑向量在不同电路拓扑中变化规律各不相同的基本事实,通过对最简拓扑向量的选取、验算及监测,可依据较少的检测量而实现电力电子电路的拓扑辨识。

With the fact that there are some topology vectors that vary with different formula in each circuit topology, another identification way can be carried out by selecting and measuring the best topology vectors.

另一方面,基于电路的拓扑向量在不同电路拓扑中变化规律各不相同的基本事实,通过对最简拓扑向量的选取、验算及监测,可依据较少的检测量而实现电力电子电路的拓扑辨识。

Based on the degree distribution and comparison identification, the topology structure of Shenyang automobile network approaches BA(m=2) scale-free network, whose two distinct qualities are growth and preferential attachment.

3通过度分布判定和比较判定得出结论,沈阳汽车产业网络的拓扑结构最趋近于"BA(m=2)无标度网络",这种网络拓扑模型具备的两个显著特征就是:增长性和择优性。

With rules for basic topology identification and underutilized links elimination, the engineering experience can be imported into the algorithm to guide the searching for practically optimal solution.

通过基准拓扑确定、冗余链路删除等规则的设置,可以在求解过程中方便的引入工程设计经验,引导算法进行高效搜索,避免考察工程上"无效"的解空间。

The model of weighted LRIV for topology error identification and the method of calculating the weighting factor are formed. It can make the weighted innovation value of the topology error branch show up and improve identifying ability for topology error in little load flow value branches.

形成加权新息识别拓扑错误的模型和权值计算方法,这种加权算法使得发生拓扑错误的支路相应的加权连支推算新息元素值加大,可以改善新息图法对于小功率支路上发生的拓扑错误的识别能力。

In the paper, the author did some research on the Graphical Model Platform of MGMS, the subsystem of MGMS. The GMP mainly has four functions as follows. The first aspect is the drawing function of micro-grid power system, including drawing power equipment, selecting power equipment and delete power equipment etc. The second aspect is the function of modifying parameters of power equipment. The third aspect is the function of topology automatic identification of the power system. The last aspect is advanced application function of GMP, including topology analysis and the real-time monitoring of the micro-grid power system which is in operation.

GMP主要要实现以下四个方面的功能:首先是设备绘图功能,包括鼠标绘制设备图元、鼠标选中设备图元、删除设备图元等基本的人机交互绘制微电网接线图功能;其次是修改已建设备的属性;再有是建立与建立的图形系统一致的电力系统网络模型,即对已绘图形的网络拓扑自动识别;最后是在此基础上的高级应用功能,包括电力系统网络拓扑的着色分析和运行数据的实时显示功能。

The Innovation Graph Technique is very good at real-time, so this paper goes deep into the research that the identification of topology change, bad data utilizing Innovation Graph Technique and its practicality in order to expand the theory of Innovation Graph Technique and supply a approach which can identify bad data and topology change in real lager-scale power network quickly and effectively.The model of the Innovation Graph is further studied in this paper.

新息图状态估计具有良好的实时性,本文对其在拓扑变化辨识、不良数据辨识及实用化方面进行了深入研究,旨在拓展新息图理论,提供快速有效的、可实用化的拓扑变化和不良数据辨识方法。

These strategies include: an improved adaptive movement penalty method which prevent ill condition matrix based numerical instability, a network topology based identification method which prevent too much tuning and a limited times skipping method of trial iteration.

在上篇中,本文给出了以下内容:第二章详细描述了最优潮流牛顿算法的实现,着重分析了牛顿法实际应用中存在着的两个主要问题:数值不稳定性和如何快速正确地识别起作用的不等式约束集,并提出了相应的处理对策。

Furthermore, the advantages of the genetic algorithm and the above single layer neural network are combined to yield a new identification technique. The network topology is employed to replace the procedure for solving the governing equation when GA is used to identify the system parameters of both the SDOF system and the MDOF system with or without noise contamination. The comparison is made between the predicted acceleration and the measured one for each case.

另外,结合类神经网路与基因演算法於结构动力参数识别,首先应用前述之单层类神经网路架构做为系统动力模式,再藉由基因演算法搜索符合该系统之权重值,然后将权重值代入网路架构以取代解微分方程式求得系统反应,最后再与量测反应做比较;同时亦利用该方法应用於进行识别含杂讯之输出入资料的系统权重值,以验证该方法应用於单自由度线性系统及多自由度线性系统识别之可行性。

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