Machine learning

the role of machines for resilient communities

Book Chapter (2022)
Author(s)

O. Kammouh (TU Delft - System Engineering)

G. P. Cimellaro (Politecnico di Torino)

Research Group
System Engineering
Copyright
© 2022 O. Kammouh, Gian Paolo Cimellaro
DOI related publication
https://doi.org/10.1061/9780784415894.ch5
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 O. Kammouh, Gian Paolo Cimellaro
Research Group
System Engineering
Pages (from-to)
231-251
ISBN (print)
9780784415894
ISBN (electronic)
9780784483756
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

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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