Title: Problems Of Emergency Forecasting
Authors: Akhmadbek Jalilov
Volume: 8
Issue: 10
Pages: 103-107
Publication Date: 2024/10/28
Abstract:
The accurate forecasting of emergencies is a critical component in mitigating risks and reducing the impact of natural and man-made disasters. This paper addresses the main challenges associated with emergency forecasting, including the complexity of predictive models, data availability, and the integration of diverse risk factors. By reviewing current forecasting methodologies, we identify key limitations in existing approaches such as the uncertainty in predicting rare events, the lack of real-time data, and difficulties in modeling multi-hazard scenarios. Furthermore, the paper explores the role of artificial intelligence and big data analytics in enhancing prediction accuracy. This study aims to provide a comprehensive understanding of these challenges and proposes strategies to improve emergency forecasting, focusing on interdisciplinary collaboration, technological advancement, and policy implementation to strengthen disaster preparedness and response systems.