• Sourabh kumar
• Mithun Mallick

Delay of flight has been regarded as one of the toughest difficulties in aviation control. This study analyses data from The U.S. Department of Transportation's (DOT) Bureau of Transportation Statistics (BTS) and proposes a method to model the arriving flights and three different regression algorithms to predict delay, and checking its accuracy with certain parameters. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide a decision basis for airport authorities. The model aims to help the authorities to predict the flight delay in order to save as much as time of the customers and also the staffs. This model increases the accuracy of the prediction and also overcomes the limitation of large data processing.

Flight delay prediction Exploratory data analysis Regression models

"Predicting delay in flights using Machine learning and Big Data ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.a128-a138, May-2021, Available :http://www.jetir.org/papers/JETIR2105016.pdf

"Predicting delay in flights using Machine learning and Big Data ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppa128-a138, May-2021, Available at : http://www.jetir.org/papers/JETIR2105016.pdf