2篇
您的检索式：作者名="Syed Basit Ali Bukhari"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Intelligent Islanding Detection of Multi-distributed Generation Using Artificial Neural Network Based on Intrinsic Mode Function Feature显示文摘The integration of distributed energy resources(DERs) into distribution networks is becoming increasingly important, as it supports the continued adoption of renewable power generation, combined heat and power plants, and storage systems. Nevertheless, inadvertent islanding operation is one of the major protection issues in distribution networks connected to DERs. This study proposes an intelligent islanding detection method(IIDM) using an intrinsic mode function(IMF)feature-based grey wolf optimized artificial neural network(GWO-ANN). In the proposed IIDM, the modal voltage signal is pre-processed by variational mode decomposition followed by Hilbert transform on each IMF to derive highly involved features. Then, the energy and standard deviation of IMFs are employed to train/test the GWO-ANN model for identifying the islanding operations from other non-islanding events. To evaluate the performance of the proposed IIDM, various islanding and non-islanding conditions such as faults, voltage sag, linear and nonlinear load and switching, are considered as the training and testing datasets. Moreover, the proposed IIDM is evaluated under noise conditions for the measured voltage signal. The simulation results demonstrate that the proposed IIDM is capable of differentiating between islanding and non-islanding events without any sensitivity under noise conditions in the test signal. | Samuel Admasie Syed Basit Ali Bukhari Teke Gush Raza Haider Chul Hwan Kim | 2020 | Journal of Modern Power Systems and Clean Energy2020，8，3： | 2 |
| 2 | 基于深度卷积神经网络的两阶段肺结节检测显示文摘针对传统肺结节检测中存在灵敏度低、假阳性高、小结节难检测的问题,提出一种基于深度卷积神经网络的两阶段肺结节检测框架。第一阶段使用特征金字塔子网提取肺部影像的多层次特征,引入多尺度区域建议子网用于在高灵敏度下检测出所有的候选结节;第二阶段设计级联卷积神经网络模型减少假阳性,通过保留分类错误样本用于重新训练模型,将多个模型结果进行投票选出最终分类结果。LUNA16数据集上的实验结果表明,所提框架灵敏度达到95.9%,检测效果优于其它算法,能够有效实现肺结节的准确检测。 | 韩鹏 强彦 刘继华 贾婧 Syed Basit Ali Shah Bukhari | 2021 | 计算机工程与设计2021，42，3： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员