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Statistics report
Nov. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 115
Paper Published : 1391
No. of Authors : 3527
  Journal Paper


Paper Title :
Comparative Study of Prediction Models for Flight Departure Delays in Airports

Author :Meghana K Murthy, Rohit Raghunathan, B. M. Sagar

Article Citation :Meghana K Murthy ,Rohit Raghunathan ,B. M. Sagar , (2019 ) " Comparative Study of Prediction Models for Flight Departure Delays in Airports " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 1-4, Volume-7, Issue-8

Abstract : This paper presents a comparative study on prediction models for flight delays in airports. Flight delay prediction is important to alleviate the cost occurred due to the same. The flight dataset has been collected from Kaggle for the O’Hare International Airport at Chicago for the year 2015.The prediction models explored in this paper include variations of gradient boosting machines, an important ensemble method for prediction analysis. The different boosters included are Tree, Linear and Dart. Each model is trained using the Caret Package in R to obtain results. Important parameters and the effect of tuning these parameters on the model prediction result are also discussed. xgbTree shows the best prediction results. Keywords - Data Analytics, Flight Delay Predictions, Gradient Boosting.

Type : Research paper

Published : Volume-7, Issue-8


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-15928   View Here

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