Machine learning

the role of machines for resilient communities

Book chapter (2022)

Authors

O. Kammouh System Engineering - TPM
Gian Paolo Cimellaro Politecnico di Torino
Research Group
System Engineering (TPM) (TU Delft)
Copyright: © 2022 O. Kammouh, Gian Paolo Cimellaro
DOI: https://doi.org/10.1061/9780784415894.ch5
More Info
expand_more

Published Date

2022

Language

English

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.

Faculty

Technology, Policy and Management

Department

Multi Actor Systems

Research Group

System Engineering

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.

Files

Objective_resilience_ASCE_ML_f... (pdf)
(pdf | 0.537 Mb)
Unknown license

Download not available

Book_5124_C005.pdf
(pdf | 0.743 Mb)
- Embargo expired in 08-10-2022
Unknown license