SCIENTIFIC BASIS FOR IMPROVING THE EMERGENCY PREDICTION SYSTEM
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Keywords: emergency situations, forecasting systems, artificial intelligence, big data, seismic activity, security, Uzbekistan.##article.abstract##
Abstract. This article examines the scientific basis for improving emergency situation (ES) forecasting systems. The study analyzes ways to increase the accuracy, speed, and efficiency of forecasting using artificial intelligence (AI) and big data technologies [1]. Studies conducted on the example of seismically active regions of Uzbekistan, in particular the Fergana Valley, have shown the advantages of new systems - 20% increased accuracy, 30% reduced time, and 80% adaptation to local infrastructure. The article emphasizes the importance of modern approaches to preventing economic and social damage from ES. At the same time, the financial and technical constraints on the implementation of AI and big data in Uzbekistan were also considered. Although the study is limited by the lack of real-world testing, it provides suggestions for future adaptation to local conditions. The article presents practical solutions for increasing security and optimizing resources.
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