This paper explores the use of machine learning (ML) and big data analytics to enhance the accuracy and efficiency of flight delay predictions. Utilizing data from the Federal Aviation Administration (FAA) covering the period from 2018 to 2022, we analyze critical factors influencing delays and ...
Ride-sharing apps like Uber and Lyft use machine learning for their dynamic pricing at times when demand is high. Airlines, hotels and e-commerce platforms also use dynamic pricing models to adjust prices in real time, often resulting in higher profits. Two of the main ways machine learning c...
Machine learning optimises transportation networks, predicts customer behaviour, and provides tailored services to improve the passenger experience. Airlines can optimise operations, improve loyalty, and increase revenue by analysing passenger data (Akerkar, 2014; Duraisamy et al., 2019; Brunton et al.,...
This Machine Learning tutorial is for anyone who wants to learn about machine learning. No prior knowledge of machine learning is required. Read the tutorial to learn more about machine learning.
Baggage and luggage: using analytics for just-in-time operations One key area where transformational technologies are making an impact now for airports, airlines and ground handlers is by better tracking the billions of bags that are transported every year. This technology is already r...
MATLAB Machine Learning Toolbox Regression Learner SVM Models Cost Optimization in Airlines Artificial Intelligence in Aviation MATLAB Optimization Toolbox Genetic Algorithm, Random Search, Pattern Search in MATLAB Contributing Contributions to enhance the project are welcome. Cite As Alireza Ghader...
Flight Delay Prediction using Hybrid Machine Learning Approach: A Case Study of Major Airlines in the United States The aviation industry has experienced constant growth in air traffic since the deregulation of the U.S. airline industry in 1978. As a result, flight delay... RK Jha,SB Jha,V...
Deep learning is a subset of machine learning that involves the use of neural networks to analyze large amounts of data and learn patterns [125]. In the context of robotics taxi services, AI, ML, and DL can be used to achieve several goals. For example: Overall, the combination of AI,...
Machine learning offers new tools to overcome challenges for which traditional statistical methods are not well-suited. This paper provides an overview of machine learning with a specific focus on supervised learning (i.e., methods that are designed to predict or classify an outcome of interest)....
“An example of this is Uber surge pricing, which ensures cars are still available by pricing some passengers out of the market while making driving more appealing for drivers.”The company uses machine learning to forecast “where, when, and how many ride requests Uber will receive at any ...