Results 21 to 30 of about 128,875 (283)
Entropy, 2023 Outlier detection is an important task in the field of data mining and a highly active area of research in machine learning. In industrial automation, datasets are often high-dimensional, meaning an effort to study all dimensions directly leads to data ...
Zihao Li, Liumei Zhang
doaj +1 more source
Measuring Novelty in Autonomous Vehicles Motion Using Local Outlier Factor Algorithm
, 2021 Under unexpected conditions or scenarios, autonomous vehicles (AV) are more likely to follow abnormal unplanned actions, due to the limited set of rules or amount of experience they possess at that time. Enabling AV to measure the degree at which their movements are novel in real-time may help to decrease any possible negative consequences.
Alsawadi, Hassan, Bilal, Muhammad
openaire +2 more sources
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
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
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
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
core +4 more sources
Detection of High-level PM<SUB>2.5</SUB> Occurrences Applying Local Outlier Factor (LOF) Algorithm
Journal of Korean Society for Atmospheric Environment, 2021 Yongchan Lee, Yongbum Kwon, Heekwan Lee
openaire +2 more sources
Predictive intelligence to the edge through approximate collaborative context reasoning [PDF]
, 2017 We focus on Internet of Things (IoT) environments where a network of sensing and computing devices are responsible to locally process contextual data, reason and collaboratively infer the appearance of a specific phenomenon (event).
Anagnostopoulos, Christos +1 more
core +1 more source
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
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
doaj +1 more source