"Go-Around Prediction in Non-Stabilized Approach Scenarios Through a ..."

Jesús Cantero et al. (2022)

> Home

Details and statistics

DOI: 10.1007/978-3-031-21753-1_48

access: closed

type: Conference or Workshop Paper

metadata version: 2022-11-22

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/ideal/CanteroCLDHIN22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/ideal/CanteroCLDHIN22
Jesús Cantero, Adrián Colomer, Laëtitia Launet, Alexandre Duchevet, Théo de la Hogue, Jean-Paul Imbert, Valery Naranjo:
Go-Around Prediction in Non-Stabilized Approach Scenarios Through a Regression Machine-Learning Model Trained from Pilots' Expertise. IDEAL 2022: 491-499

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.