Abstract
The application of data fusion for disaster prediction using GPT (Generative Pre-trained Transformer) is covered in this study. Data fusion is the process of merging information from several sources including social media, sensor data, and simulation data, in order to increase the precision of catastrophe prediction models. Through the utilization of GPT, an artificial intelligence language model, data fusion enables a thorough examination and amalgamation of data from disparate fields, hence producing more resilient forecasts. GPT models may be used to recognize geographical descriptions from social media postings and identify cell kinds using information about marker genes. Proactive communication with impacted people in times of catastrophe is made possible by the integration of GPT with social media monitoring. GPT models may significantly enhance disaster preparedness, response, prediction, and recovery by gathering pertinent data from many sources and modelling various situations.
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