FLIGHT DELAY ANALYSIS AND PREDICTION

Abstract

Flight delays are a common problem in the aviation industry and can affect passengers, airlines, airport operations, and overall transportation efficiency. Delays may occur due to several factors, including weather conditions, air traffic congestion, aircraft-related issues, airport operations, and scheduling constraints. Analyzing historical flight data can help identify patterns associated with delays and support better operational planning. The Flight Delay Analysis and Prediction system is designed to analyze historical flight records and identify the factors that contribute to flight delays. The system uses information such as airline, origin airport, destination airport, scheduled departure time, arrival time, flight duration, weather conditions, and previous delay information. Data preprocessing techniques are applied to clean and prepare the dataset for analysis. The system performs sexploratory data analysis to identify delay patterns across airlines, airports, routes, time periods, and other relevant factors. Visualization techniques such as bar charts, line graphs, heatmaps, and dashboards can be used to represent delay distributions and trends. These visualizations help users understand which factors are associated with higher or lower delay frequencies. A Machine Learning model is used to predict whether a particular flight is likely to experience a delay based on available input features. Classification algorithms can be trained using historical flight records and evaluated using suitable performance metrics. The system can display the prediction along with relevant analytical information to help users understand the result. Overall, the proposed system combines historical flight-data analysis with predictive modeling to provide useful insights into flight delays. It can support airlines, airport analysts, researchers, and other authorized users in understanding delay patterns and improving operational planning. Future enhancements can include real-time flight data, live weather information, advanced time-series models, route-specific prediction, and real-time delay alerts.