About this document

FDM Unknown Hazards Detection Techniques by Pedro Rossel Alarcón is a document available to read on EtoBox.

This document discusses using clustering techniques and autoencoders to detect unknown hazards during the approach phase of flights. It proposes applying clustering to identify patterns in approach data and detect outlier flights. It also suggests using autoencoders, a type of neural network, to learn what normal approaches look like in order to identify abnormal flights based on their reconstruction error. The methodology aims to help safety experts analyze flight data without relying solely on rule-based

Author

Pedro Rossel Alarcón

Language

EN