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Prediction of Delay in Flights using AI Techniques: A Review
Author Name : Sarika Gupta, Manish Kumar Singhal
ABSTRACT Flight delays are a persistent challenge for the aviation industry, affecting passengers, airlines, and airport operations worldwide. Predicting delays in advance can significantly improve resource management, enhance passenger satisfaction, and optimize airline operations. Artificial Intelligence (AI) techniques, such as machine learning and deep learning, have emerged as promising tools for accurately predicting flight delays by analyzing vast datasets with complex patterns. This review provides a comprehensive examination of AI-based methods used in delay prediction, focusing on techniques like regression models, neural networks, decision trees, and ensemble learning approaches. The paper explores the integration of data sources, including weather conditions, air traffic, flight schedules, and historical delay records, to enhance prediction accuracy