Results 11 to 20 of about 52,299 (258)
Outlier Detection Credit Card Transactions Using Local Outlier Factor Algorithm (LOF)
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2019 Threats or fraud for credit card owners and banks as service providers have been harmed by the actions of perpetrators of credit card thieves. All transaction data are stored in the bank's database, but are limited in information and cannot be used as a ...
Silvano Sugidamayatno, Danang Lelono
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Electricity Theft Detection in AMI Based on Clustering and Local Outlier Factor [PDF]
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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The Network Link Outlier Factor (NLOF) for Fault Localization [PDF]
IEEE Open Journal of the Communications Society, 2020 We describe and experimentally evaluate the performance of our Network Link Outlier Factor (NLOF) for locating faults in communication networks. The NLOF is a unique outlier score assigned to each link in a network. It is computed using four distinct stages in a data analytics pipeline.
Christopher Mendoza, Michael P. McGarry
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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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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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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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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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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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A Two-Level Approach based on Integration of Bagging and Voting for Outlier Detection
Journal of Data and Information Science, 2020 The main aim of this study is to build a robust novel approach that is able to detect outliers in the datasets accurately. To serve this purpose, a novel approach is introduced to determine the likelihood of an object to be extremely different from the ...
Dogan Alican, Birant Derya
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Energies, 2023 The accurate detection of wind power outliers plays a crucial role in wind power forecasting, while the inherited strong randomness and high fluctuations bring great challenges to this issue.
Jingtao Huang, Jin Qin, Shuzhong Song
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