Data-driven runway occupancy time prediction using decision trees

• المؤلفون الرئيسيون: Chow, Hong Wei, Lim, Zhi Jun, Alam, Sameer
• مؤلفون آخرون: School of Mechanical and Aerospace Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2021
• الموضوعات: Engineering::Aeronautical engineering::Aviation; Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Runway Occupancy Time; Machine Learning; Decision Tree
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/153282
• المؤسسة: Nanyang Technological University

With an increasing amount of flights, the demand for runways at airports increases as well. Innovative mechanisms are required to maximise the use of a runway such that the demand can be met. Such mechanisms include the prediction of Runway Occupancy Time (ROT), so that the Air Traffic Controllers (...