Chapter 5
Machine Learning: The Role of Machines for Resilient Communities
Publication: Objective Resilience: Objective Processes
Abstract
This chapter introduces the role of machine learning (ML) in resilience engineering and discusses actual cases of emergencies in which ML contributed positively. To identify its benefits within the resilience-relevant aspects (social, economic, infrastructural, institutional, environmental, and communitywise), the role of ML in various disaster management applications is analyzed, including model identification, emergency detection, and solution generation. The problem of data scarcity in model identification is presented. The application of ML in different fields of emergency detection (e.g., physical, virtual) is highlighted. Finally, the effectiveness of ML in solution generation to support human decision making is evaluated. Real examples are included in which machines exceed humans in providing solutions.
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Acknowledgments
The research leading to these results has received funding from the European Research Council under the Grant Agreement n° ERC_IDEAL RESCUE_637842 of the project IDEAL RESCUE—Integrated Design and Control of Sustainable Communities during Emergencies.
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Published In
Objective Resilience: Objective Processes
Pages: 231 - 251
Editor: Mohammed M. Ettouney, Ph.D. https://orcid.org/0000-0001-7287-5090
ISBN (Print): 978-0-7844-1589-4
ISBN (Online): 978-0-7844-8375-6
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© 2022 American Society of Civil Engineers.
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Published online: Apr 8, 2022
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