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Application of Machine Learning Algorithms in the Mitigation Phase of Disaster Management: A Review

Application of Machine Learning Algorithms in the Mitigation Phase of Disaster Management: A Review

Elrich Joshua Miranda, Kaushhal Narayanaswami Kumarji, Srilakshmi Ramesan, Thomas Varghese, Vinay V. Panicker, Devendra K. Yadav
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 13
ISSN: 1947-8402|EISSN: 1947-8410|EISBN13: 9781683181989|DOI: 10.4018/IJSESD.292079
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MLA

Miranda, Elrich Joshua, et al. "Application of Machine Learning Algorithms in the Mitigation Phase of Disaster Management: A Review." IJSESD vol.13, no.1 2022: pp.1-13. http://doi.org/10.4018/IJSESD.292079

APA

Miranda, E. J., Kumarji, K. N., Ramesan, S., Varghese, T., Panicker, V. V., & Yadav, D. K. (2022). Application of Machine Learning Algorithms in the Mitigation Phase of Disaster Management: A Review. International Journal of Social Ecology and Sustainable Development (IJSESD), 13(1), 1-13. http://doi.org/10.4018/IJSESD.292079

Chicago

Miranda, Elrich Joshua, et al. "Application of Machine Learning Algorithms in the Mitigation Phase of Disaster Management: A Review," International Journal of Social Ecology and Sustainable Development (IJSESD) 13, no.1: 1-13. http://doi.org/10.4018/IJSESD.292079

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Abstract

The Mitigation phase in disaster management (DM) is a widely researched subject, and rightly so due to its invaluable role in dampening the consequences of disasters on life and property. A successful mitigation phase serves to be a solid foundation for the smooth execution of the subsequent phases in DM. This paper looks at some of the recent studies and developments pertinent to the mitigation phase in DM, in an attempt to deduce the prevalent Machine Learning (ML) Techniques that are employed across various disaster scenarios. The paper also looks into some of the key factors that have to be considered to ensure a sustainable plan for mitigation.

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