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              <text>Artificial Intelligence in Disaster Management: A Survey</text>
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              <text>Disaster management; Disaster mitigation; Disaster preparedness; Disaster recovery; Disaster response; Machine learning</text>
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              <text>This paper provides a literature review of cutting-edge artificial intelligence-based methods for disaster management. Most governments are worried about disasters, which, in general, are unbelievable events. Researchers tried to deploy numerous artificial intelligence (AI)-based approaches to eliminate disaster management at different stages. Machine learning (ML) and deep learning (DL) algorithms can manage large and complex datasets emerging intrinsically in disaster management circumstances and are incredibly well suited for crucial tasks such as identifying essential features and classification. The study of existing literature in this paper is related to disaster management, and further, it collects recent development in nature-inspired algorithms (NIA) and their applications in disaster management.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <text>Arora S.; Kumar S.; Kumar S.</text>
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              <text>Lecture Notes in Networks and Systems, Vol-552, pp. 793-805.</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-19-6634-7_56" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-6634-7_56&lt;/a&gt;
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              <text>ISSN: 23673370; ISBN: 978-981196633-0</text>
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              <text>Arora S., Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Kumar S., Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India</text>
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