Results 21 to 30 of about 19,165 (241)
Fast Outlier Detection Using a Grid-Based Algorithm. [PDF]
PLoS ONE, 2016 As one of data mining techniques, outlier detection aims to discover outlying observations that deviate substantially from the reminder of the data. Recently, the Local Outlier Factor (LOF) algorithm has been successfully applied to outlier detection ...
Jihwan Lee, Nam-Wook Cho
doaj +1 more source
Density-Distance Outlier Detection Algorithm Based on Natural Neighborhood
Axioms, 2023 Outlier detection is of great significance in the domain of data mining. Its task is to find those target points that are not identical to most of the object generation mechanisms.
Jiaxuan Zhang, Youlong Yang
doaj +1 more source
Application of Local Outlier Factor Algorithm to Detect Anomalies in Computer Network
Elektronika ir Elektrotechnika, 2018 Gap between the new attack appearance and signature creation for this attack may be critical. During this time, many computer systems may be affected and valuable resources may be lost. Even after signature creation, many computer systems still stay vulnerable because of bad security practice, i.e.
Auškalnis, Juozas +2 more
openaire +3 more sources
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
doaj +1 more source
Hybrid Machine Learning–Statistical Method for Anomaly Detection in Flight Data
Applied Sciences, 2022 This paper investigates the use of an unsupervised hybrid statistical–local outlier factor algorithm to detect anomalies in time-series flight data. Flight data analysis is an activity carried out by airlines primarily as a means of improving the safety ...
Sameer Kumar Jasra +3 more
doaj +1 more source
TADILOF: Time Aware Density-Based Incremental Local Outlier Detection in Data Streams
Sensors, 2020 Outlier detection in data streams is crucial to successful data mining. However, this task is made increasingly difficult by the enormous growth in the quantity of data generated by the expansion of Internet of Things (IoT).
Jen-Wei Huang +2 more
doaj +1 more source
Scientific Reports, 2022 White matter lesions (WML) underlie multiple brain disorders, and automatic WML segmentation is crucial to evaluate the natural disease course and effectiveness of clinical interventions, including drug discovery.
Kokhaur Ong +9 more
doaj +1 more source
Abrupt user load change detection based on multiple features and LOF algorithm
Zhejiang dianli, 2023 The sudden load changes impact power grids by frequency and power oscillations. In order to distinguish the complex and massive abnormal user load data， this paper proposes a method combining multiple features and LOF （local outlier factor） algorithm ...
ZENG Jing +4 more
doaj +1 more source
Applied Computational Intelligence and Soft Computing, 2022 Data clustering algorithms experience challenges in identifying data points that are either noise or outlier. Hence, this paper proposes an enhanced connectivity measure based on the outlier detection approach for multi-objective data clustering problems.
Hossam M. J. Mustafa, Masri Ayob
doaj +1 more source
Model-free detection of unique events in time series
Scientific Reports, 2022 Recognition of anomalous events is a challenging but critical task in many scientific and industrial fields, especially when the properties of anomalies are unknown.
Zsigmond Benkő +2 more
doaj +1 more source