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Predicting natural disasters with AI and machine learning

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Predicting natural disasters with AI and machine learning/ D. Satishkumar, M. Sivaraja, editors.
其他題名:	Predicting natural disasters with artificial intelligence and machine learning
其他作者:	Muthusamy, Sivaraja,
出版者:	Hershey, Pennsylvania :IGI Global, : 2024,
面頁冊數:	1 online resource (340 p.)
內容註:	Chapter 1. Unravelling complications in natural disasters: a comprehensive exploration -- Chapter 2. Reshaping disaster resilience: the AI and machine learning revolution in natural catastrophe management -- Chapter 3. Navigating the crescendo of challenges in harnessing artificial intelligence for disaster management -- Chapter 4. The impact of social media on public perception and behaviour during disasters: an AI-enhanced analysis -- Chapter 5. Future trends and innovations in natural disaster detection using AI and ML -- Chapter 6. Artificial intelligence and IoT-based disaster management system -- Chapter 7. Prediction analysis of natural disasters using machine learning -- Chapter 8. Predicting tropical cyclones: a supervised machine learning approach -- Chapter 9. Futuristic disaster mitigation: the role of gpus and AI accelerators -- Chapter 10. IoT-based smart sensors: the key to early warning systems and rapid response in natural disasters -- Chapter 11. Automation of IOT robotics -- Chapter 12. Mitigating disasters below the surface: a comprehensive study on recent advantages and ongoing challenges in underwater sensor networks -- Chapter 13. Unveiling earth's rhythms: deep learning techniques for forecasting seismic cycle locations -- Chapter 14. A comprehensive machine learning approach for accurate forest fire forecasting.
標題:	Natural disasters - Forecasting. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-2280-2
ISBN:	9798369322819

Predicting natural disasters with AI and machine learning
Predicting natural disasters with AI and machine learning[electronic resource] /Predicting natural disasters with artificial intelligence and machine learningD. Satishkumar, M. Sivaraja, editors. - Hershey, Pennsylvania :IGI Global,2024 - 1 online resource (340 p.)

Includes bibliographical references and index.

Chapter 1. Unravelling complications in natural disasters: a comprehensive exploration -- Chapter 2. Reshaping disaster resilience: the AI and machine learning revolution in natural catastrophe management -- Chapter 3. Navigating the crescendo of challenges in harnessing artificial intelligence for disaster management -- Chapter 4. The impact of social media on public perception and behaviour during disasters: an AI-enhanced analysis -- Chapter 5. Future trends and innovations in natural disaster detection using AI and ML -- Chapter 6. Artificial intelligence and IoT-based disaster management system -- Chapter 7. Prediction analysis of natural disasters using machine learning -- Chapter 8. Predicting tropical cyclones: a supervised machine learning approach -- Chapter 9. Futuristic disaster mitigation: the role of gpus and AI accelerators -- Chapter 10. IoT-based smart sensors: the key to early warning systems and rapid response in natural disasters -- Chapter 11. Automation of IOT robotics -- Chapter 12. Mitigating disasters below the surface: a comprehensive study on recent advantages and ongoing challenges in underwater sensor networks -- Chapter 13. Unveiling earth's rhythms: deep learning techniques for forecasting seismic cycle locations -- Chapter 14. A comprehensive machine learning approach for accurate forest fire forecasting.

"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."--

ISBN: 9798369322819Subjects--Topical Terms:

707431
Natural disasters
--Forecasting.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: GB5014 / .P74 2024e

Dewey Class. No.: 363.34/72

Predicting natural disasters with AI and machine learning
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504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Unravelling complications in natural disasters: a comprehensive exploration -- Chapter 2. Reshaping disaster resilience: the AI and machine learning revolution in natural catastrophe management -- Chapter 3. Navigating the crescendo of challenges in harnessing artificial intelligence for disaster management -- Chapter 4. The impact of social media on public perception and behaviour during disasters: an AI-enhanced analysis -- Chapter 5. Future trends and innovations in natural disaster detection using AI and ML -- Chapter 6. Artificial intelligence and IoT-based disaster management system -- Chapter 7. Prediction analysis of natural disasters using machine learning -- Chapter 8. Predicting tropical cyclones: a supervised machine learning approach -- Chapter 9. Futuristic disaster mitigation: the role of gpus and AI accelerators -- Chapter 10. IoT-based smart sensors: the key to early warning systems and rapid response in natural disasters -- Chapter 11. Automation of IOT robotics -- Chapter 12. Mitigating disasters below the surface: a comprehensive study on recent advantages and ongoing challenges in underwater sensor networks -- Chapter 13. Unveiling earth's rhythms: deep learning techniques for forecasting seismic cycle locations -- Chapter 14. A comprehensive machine learning approach for accurate forest fire forecasting.
520 3 $a "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."-- $c Provided by publisher.
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