Hybrid Machine Learning–Statistical Method for Anomaly Detection in Flight Data

Hybrid Machine Learning–Statistical Method for Anomaly Detection in Flight Data

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 and operation of their fleet. Traditionally, t...

Full description

Bibliographic Details
Main Authors: Sameer Kumar Jasra, Gianluca Valentino, Alan Muscat, Robert Camilleri
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
unsupervised anomaly detection
time series anomaly detection
local outlier factor
Tukey’s method
flight data analysis
Online Access:https://www.mdpi.com/2076-3417/12/20/10261

Internet

https://www.mdpi.com/2076-3417/12/20/10261

Similar Items