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Predicting Natural Disasters With Ai And Machine Learning 1st Edition D Satishkumar

  • SKU: BELL-171183840
Predicting Natural Disasters With Ai And Machine Learning 1st Edition D Satishkumar
$ 31.00 $ 45.00 (-31%)

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Predicting Natural Disasters With Ai And Machine Learning 1st Edition D Satishkumar instant download after payment.

Publisher: Engineering Science Reference
File Extension: PDF
File size: 2.61 MB
Pages: 360
Author: D. Satishkumar, M. Sivaraja
ISBN: 9798369322802, 8369322808
Language: English
Year: 2024
Edition: 1

Product desciption

Predicting Natural Disasters With Ai And Machine Learning 1st Edition D Satishkumar by D. Satishkumar, M. Sivaraja 9798369322802, 8369322808 instant download after payment.

"This book explores various AI and ML applications designed to predict, manage, and mitigate the impact of natural disasters, focusing on natural language processing, and early warning systems"--In a world where the relentless force of natural and man-made disasters threatens societies, the need for effective disaster management has never been more critical. Predicting Natural Disasters With AI and Machine Learning addresses the challenges of disasters and charts a path toward proactive solutions by applying artificial intelligence (AI) and machine learning (ML). This book begins by interpreting the nature of disasters, clearly distinguishing between natural and man-made hazards. It delves into the intricacies of disaster risk reduction (DRR), emphasizing the human contribution to most disasters. Recognizing the necessity for a multifaceted approach, the book advocates the four 'R's - Risk Mitigation, Response Readiness, Response Execution, and Recovery - as integral components of comprehensive disaster management. This book explores various AI and ML applications designed to predict, manage, and mitigate the impact of natural disasters, focusing on natural language processing, and early warning systems. The contrast between weak AI, simulating human intelligence for specific tasks, and strong AI, capable of autonomous problem-solving, is thoroughly examined in the context of disaster management. Its chapters systematically address critical issues, including real-world data handling, challenges related to data accessibility, completeness, security, privacy, and ethical considerations.

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