Flight Delay Prediction Using Deep Learning and Conversational Voice-Based Agents

Authors

  • Sia Gholami The Institute of Electrical and Electronics Engineers, Member IEEE
  • Saba Khashe The Institute of Electrical and Electronics Engineers, Member IEEE

Keywords:

Flight Delays, Machine Learning, Deep Learning, Predictions, Regression

Abstract

Airlines are critical today for carrying people and commodities on time. Any delay in the schedule of these planes can potentially disrupt the business and trade of thousands of employees at any given time. Therefore, precise flight delay prediction is beneficial for the aviation industry and passenger travel. Recent research has focused on using artificial intelligence algorithms to predict the possibility of flight delays. Earlier prediction algorithms were designed for a specific air route or airfield. Many present flight delay prediction algorithms rely on tiny samples and are challenging to understand, allowing almost no room for machine learning implementation. This research study develops a flight delay prediction system by analyzing data from domestic flights inside the United States of America. The proposed models learn about the factors that cause flight delays and cancellations and the link between departure and arrival delays.

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Published

2022-08-16

How to Cite

Sia Gholami, & Saba Khashe. (2022). Flight Delay Prediction Using Deep Learning and Conversational Voice-Based Agents. American Scientific Research Journal for Engineering, Technology, and Sciences, 89(1), 60–72. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/7894

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Articles