Prediction of Inbound and Outbound Flight Delays Based on Random Forest
In order to predict the inbound and outbound flight delays scientifically and effectively,this paper selects the char-acteristic factors such as airport busyness,flight distance,weather and ground service guarantee time,analyzes the relationship be-tween each characteristic factor and flight delays,and quantifies the characteristic factors.The ratio of aircraft takeoffs and landings per unit hour at the airport is used to quantify the airport busyness.The actual value of navigation distance is quantified by consider-ing the influence of aircraft navigation in the air by control.The ATMAP algorithm is used to score and quantify the METAR messag-es,and the ground service guarantee time in A-CDM is used to digitize them.The above characteristic factors are coded into the pre-diction model,and the random forest algorithm is used to build the model,and the short-term delay prediction is made for each in-coming flight and departing flight in an airport respectively.The experimental results show that 85.7%of inbound flight delay predic-tions have a difference of less than 15 minutes from the actual value,83.7%of departing flight delay predictions have a difference of less than 15 minutes from the actual value.This provides a decision basis for airports,airlines and ATC.
random forest regressiondelay predictionATMAP algorithmairport busyness
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