Akademik Veri Yönetim Sistemi
Journal of aviation (Online), cilt.9, sa.3, ss.609-613, 2025 (TRDizin)
The landing phase, one of the flight phases, is considered the most critical phase due to its significantly higher accident rate compared to other flight phases. A large portion of accidents occurring during the landing phase consists of hard landings. A hard landing is a landing incident defined as the main landing gear impacting the ground with a greater vertical speed and force than a normal landing. The severity of hard landings can vary from minor passenger discomfort to serious aircraft damage, structural failure, or even loss of life. In this study, the decision-making process regarding go-around maneuvers based on hard landing prediction is addressed using Machine Learning methods, specifically Logistic Regression and Random Forest models. Modeling was conducted using a dataset composed of real-time flight parameters, aiming to prevent hard landing incidents and even landing accidents. The calculation results indicate that the developed models provide accurate predictions for hard landing events.