Flight Minder: Enhancing Flight Delay Prediction

Abstract

The objective of the proposed Flight Delay system is to apply machine learning techniques to accurately predict flight delays, improving the efficiency and reliability of flight scheduling for passengers and airlines. The algorithm utilizes historical flight data, weather patterns, and other relevant factors to predict the likelihood and duration of flight delays. By analysing past flight delays and their contributing factors, the system can identify patterns and trends to make more accurate predictions. Extensive testing and evaluation demonstrate the effectiveness of the Flight Delay system in accurately predicting flight delays. Model performance is evaluated using metrics such as precision, recall, and F1-score, with the findings indicating significant improvements over traditional methods. Real-world validation using diverse datasets further confirms the system's reliability and potential to enhance flight scheduling and passenger experience.