A Novel Approach for Flight Delay Prediction Using AI
Keywords:
Decision Tree Regression, Bayesian Ridge, Random Forest Regression, and Gradient Boosting Regression.Abstract
Predicting flight delays accurately is essential for building a more effective airline industry. Increasing client happiness is a key component of the airline company. All participants in commercial aviation must consider their prediction while making decisions. Flights are delayed and cause consumer displeasure due to inclement weather, a mechanical issue, and the delayed arrival of the aircraft at the place of departure. With the aid of weather and flight data, a predictive model for flights arriving on time is put forth. In this study, we forecast whether a specific flight's arrival will be delayed or not using machine learning models such Decision Tree Regression, Bayesian Ridge, Random Forest Regression, and Gradient Boosting Regression.
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