E-PILOTS: A SYSTEM TO PREDICT HARD LANDING DURING THE APPROACH PHASE OF COMMERCIAL FLIGHTS

Main Article Content

Anusha M ,Tirupati Rao S , Mahendar J

Abstract

By performing a go-around, more than half of all business aeroplane operation errors may have been avoided. Making a prompt choice to do a go-around manoeuvre may help to lower the overall accident rate in the aviation industry. In this paper, we define a cockpit-deployable equipment learning system to support flight staff decision-making for a go-around based on the forecast of a difficult touchdown event. In order to forecast challenging touchdowns, this work offers a hybrid approach that uses attributes that model the temporal dependencies of aircraft data as inputs to a semantic network. Based on a large dataset of 58177 commercial flights, the findings indicate that our technique has an average level of sensitivity and uniqueness at the go-around point of 85% and 74%, respectively. It follows that our strategy outperforms other approaches and can be deployed in the cockpit.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Article Details

How to Cite
Anusha M ,Tirupati Rao S , Mahendar J. (2023). E-PILOTS: A SYSTEM TO PREDICT HARD LANDING DURING THE APPROACH PHASE OF COMMERCIAL FLIGHTS. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 14(03), 616–622. https://doi.org/10.17762/turcomat.v14i03.14099
Section
Research Articles