USING ARTIFICIAL INTELLIGENCE IN WEATHER FORECASTING TO ENSURE SAFE LANDING

Authors

  • Z. Z. Shamsiev Department of Air Navigation Systems, Faculty of Aviation Transport Engineering, Tashkent State Transport University, Tashkent, Uzbekistan. Tashkent, Mirabad district, st. Temiryo‘lchilar, 1.

Keywords:

Artificial intelligence (AI), advanced analytics, create a decision support system (DSS), Implement recurrent neural networks (RNNs) or long short-term memory networks (LSTMs).

Abstract

Weather forecasting has long been a cornerstone in aviation safety, particularly during critical phases of flight such as landing. Unfavorable weather conditions like strong winds, low visibility, thunderstorms, and turbulence can jeopardize the safety of aircraft and passengers. Traditionally, meteorologists and aviation professionals have relied on various technologies and models for weather prediction, but the complexities and uncertainties in atmospheric conditions continue to pose challenges. Recent advancements in artificial intelligence (AI) offer promising solutions to enhance weather forecasting accuracy and reliability. By leveraging AI algorithms, machine learning models, and vast amounts of meteorological data, we can improve the precision of weather predictions, especially for the critical moments of landing. AI's ability to detect patterns, predict rare events, and continuously learn from new data makes it a transformative tool for ensuring safe landings, even in rapidly changing or challenging weather conditions. This article explores the integration of AI into weather forecasting systems with a specific focus on its application for landing safety. We will delve into the methodologies, technologies, and challenges associated with this AI-driven approach and examine the benefits it offers to the aviation industry.

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Published

2024-10-16

How to Cite

Z. Z. Shamsiev. (2024). USING ARTIFICIAL INTELLIGENCE IN WEATHER FORECASTING TO ENSURE SAFE LANDING. Web of Technology: Multidimensional Research Journal, 2(10), 39–43. Retrieved from https://webofjournals.com/index.php/4/article/view/1912

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Section

Articles