• keerthana c shekar

The science of managing air traffic flow necessitates extensive study into the topic of traffic flow prediction. There is currently a lack of attention paid to the impact of topological aviation linkages on traffic flow at a single airport in the existing literature. The Air Force's escalating toil Transportation networks are becoming more complicated due to the increasing use of unmanned aerial vehicles and general aviation aircraft (GAAs). It is now possible to follow and monitor aerial vehicles in real time and with high accuracy thanks to ADS-B technology, which has been developed to the highest level. Machine learning techniques can be used to count and estimate how much air traffic will be moving between cities using a dataset that has already been analyzed and information that has been extracted and mapped to the routes.

Air traffic flow management, Machine Learning, Regression, surveillance-broadcast (ADS-B), Air Traffic analysis etc.

"A STUDY ON AIR TRAFFIC DATA FOR AIR TRAFFIC FLOW ANALYSIS UTILIZING MACHINE LEARNING AND REGRESSION APPROACHES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 7, page no.e295-e301, July-2022, Available :http://www.jetir.org/papers/JETIR2207438.pdf

"A STUDY ON AIR TRAFFIC DATA FOR AIR TRAFFIC FLOW ANALYSIS UTILIZING MACHINE LEARNING AND REGRESSION APPROACHES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 7, page no. ppe295-e301, July-2022, Available at : http://www.jetir.org/papers/JETIR2207438.pdf