eprintid: 13852
rev_number: 7
eprint_status: archive
userid: 5
dir: disk0/00/01/38/52
datestamp: 2016-09-30 09:23:56
lastmod: 2021-08-27 17:41:36
status_changed: 2016-09-30 09:23:56
type: book_section
metadata_visibility: show
item_issues_count: 1
creators_name: Schwind, N.
creators_name: Minami, K.
creators_name: Maruyama, H.
creators_name: Ilmola-Sheppard, L.
creators_name: Inoue, K.
creators_id: 8449
title: Computational framework of resilience
ispublished: pub
divisions: prog_asa
abstract: Many researchers have been studying the resilience in urban cities. However, due to the complexity of the system involving human activities, it is difficult to define the resilience of an urban area quantitatively. We introduce an abstract model that represents an urban system through a set of variables and a utility function (or dually, a cost function) evaluating the “quality” of the states of the variables. This cost function depends on the criterion of interest for evaluating the resilience of the system, and can be easily defined in a succinct way. Then, our contribution is mainly twofold. First, we propose several performance metrics that evaluate how resilient a given system has been in some specific scenario, that is, in the past. Second, assuming we are given some knowledge about the dynamics of the system, we model its possible evolutions by embedding it into a discrete state transition machine, and show how we can adapt the performance metrics to this framework to predict the resilience of the system in the future. Such an adaptation of a performance metric to our dynamic model is called here a performance-based competency metric. This new kind of metric is useful to validate existing competency metrics (Ilmola in Competency metric of economic resilience. Urban resilience: a transformative approach. Springer, 2016) by aligning these competency metrics with our performance-based ones.
date: 2016
date_type: published
publisher: Springer International Publishing
id_number: 10.1007/978-3-319-39812-9_12
creators_browse_id: 132
full_text_status: none
place_of_pub: Cham, Switzerland
pagerange: 239-257
refereed: TRUE
isbn: 978-3-319-39812-9
issn: 1613-5113
book_title: Urban Resilience. A Transformative Approach
coversheets_dirty: FALSE
fp7_type: info:eu-repo/semantics/bookPart
citation:   Schwind, N., Minami, K., Maruyama, H., Ilmola-Sheppard, L. <https://pure.iiasa.ac.at/view/iiasa/132.html>, & Inoue, K.  (2016).  Computational framework of resilience.    In:  Urban Resilience. A Transformative Approach.  pp. 239-257 Cham, Switzerland: Springer International Publishing.  ISBN 978-3-319-39812-9 10.1007/978-3-319-39812-9_12 <https://doi.org/10.1007/978-3-319-39812-9_12>.