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.
