An Outlier Detection Approach Based on Improved Self-Organizing Feature Map Clustering Algorithm
IEEE Access, 2019 Local Outlier Factor (LOF) outlier detecting algorithm has good accuracy in detecting global and local outliers. However, the algorithm needs to traverse the entire dataset when calculating the local outlier factor of each data point, which adds extra ...
Ping Yang +4 more
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Dynamic graph embedding for outlier detection on multiple meteorological time series.
PLoS ONE, 2021 Existing dynamic graph embedding-based outlier detection methods mainly focus on the evolution of graphs and ignore the similarities among them. To overcome this limitation for the effective detection of abnormal climatic events from meteorological time ...
Gen Li, Jason J Jung
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Zhongguo Jianchuan Yanjiu, 2022 ObjectivesIn response to the increasing depth of research and design on liquefied natural gas (LNG) ship structures, higher requirements are put forward for a reliability analysis method that can quickly and accurately evaluate uncertain factors.
Xuejian LI +3 more
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Robust Incremental Outlier Detection Approach Based on a New Metric in Data Streams
IEEE Access, 2021 Detecting outliers in real time from multivariate streaming data is a vital and challenging research topic in many areas. Recently introduced the incremental Local Outlier Factor (iLOF) approach and its variants have received considerable attention as ...
Ali Degirmenci, Omer Karal
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Electricity Theft Detection in AMI Based on Clustering and Local Outlier Factor
IEEE Access, 2021 As one of the key components of smart grid, advanced metering infrastructure (AMI) provides an immense number of data, making technologies such as data mining more suitable for electricity theft detection.
Yanlin Peng +6 more
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Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder [PDF]
, 2018 Estimates of the Hubble constant, H0, from the local distance ladder and from the cosmic microwave background (CMB) are discrepant at the ∼3-σ level, indicating a potential issue with the standard ΛCDM cosmology.
Dalmasso, N, Feeney, SM, Mortlock, DJ
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An Efficient Density-Based Local Outlier Detection Approach for Scattered Data
IEEE Access, 2019 After the local outlier factor was first proposed, there is a large family of local outlier detection approaches derived from it. Since the existing approaches only focus on the extent of overall separation between an object and its neighbors, and ignore
Shubin Su +6 more
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Energy Reports, 2023 The missing and abnormal data in power transformer operation and monitoring greatly affect the accuracy of fault diagnosis and thus threaten the stable operation of power systems.
Dexu Zou +9 more
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Discrimination among Winding Mechanical Defects in Transformer Using Noise Detection and Data Mining Boosting Method [PDF]
International Journal of Industrial Electronics, Control and Optimization, 2021 IIn this paper, an efficient method to detect and discriminate mechanical defects of transformer winding based on extracting the winding frequency responses using outlier data detection and ensemble algorithms ,which in total constitutes an efficient ...
Zahra Moravej +2 more
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Implementation and assessment of two density-based outlier detection methods over large spatial point clouds [PDF]
, 2018 Several technologies provide datasets consisting of a large number of spatial points, commonly referred to as point-clouds. These point datasets provide spatial information regarding the phenomenon that is to be investigated, adding value through ...
Fissore, Francesca +3 more
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