Research Article
Volume 5 Issue 1
Pranthi Cavuturu, Muhammad Haris and Hussain Kaide Johar Manasi*
June 26, 2024
Abstract
The airline industry faces the persistent challenge of flight delays, resulting in financial losses and reduced customer satisfaction. Delta Airlines, with its primary operations centered at Hartsfield-Jackson Atlanta International Airport, encounters difficulties in effectively predicting and managing these delays. Accurate delay prediction is essential for optimizing operational efficiency, improving passenger experience, and maintaining competitiveness within the airline industry. This project focuses on the development of predictive models to forecast flight delays for Delta Airlines departures from this major hub by leveraging historical flight data. Through the use of machine learning and predictive models, the study aims to provide valuable insights and strategies for Delta Airlines to enhance strategic planning, regulatory compliance, and overall operational performance. The results of this project have the potential to contribute significantly to the airline’s efforts in mitigating flight delays and improving customer satisfaction.
Keywords: Prediction; Delay; Flights; Airlines; SARIMA; Prophet; LSTM
References