Scipediacontent: Scipediacontent moved page Draft Content 945214558 to Nesi et al 2016a

2021-02-08T09:25:49Z

Scipediacontent moved page Draft Content 945214558 to Nesi et al 2016a

Scipediacontent: Created page with " == Abstract == Today, managing critical infrastructure resilience in smart city is a challenge that can be undertaken by adopting a new class of smart tools, which are able..."

2021-02-08T09:25:46Z

Created page with " == Abstract == Today, managing critical infrastructure resilience in smart city is a challenge that can be undertaken by adopting a new class of smart tools, which are able..."

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== Abstract ==

Today, managing critical infrastructure resilience in smart city is a challenge that can be undertaken by adopting a new class of smart tools, which are able to integrate modeling capability with evidence driven decision support. The Resilience Decision Support tool, as presented in this article, is an innovative and powerful tool that aims at managing critical infrasctructure resilience through a more complex and expressive model based on the Functional Resonance Analysis Method and through the connection of such a model with a system thinking based decision support tool exploiting smart city data. Thanks to ResilienceDS, FRAM model becomes computable and the functional variability that is at the core of the resilience analysis can be quantified. Such quantification allows the decision support tool to compute specific strategies and recommendations for variability dampening at strategic, tactic and operational stage. The solution has been developed in the context of RESOLUTE H2020 project of the European Commission.

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1109/isc2.2016.7580833 http://dx.doi.org/10.1109/isc2.2016.7580833]

* [http://hdl.handle.net/11591/417885 http://hdl.handle.net/11591/417885]

* [http://xplorestaging.ieee.org/ielx7/7573871/7580726/07580833.pdf?arnumber=7580833 http://xplorestaging.ieee.org/ielx7/7573871/7580726/07580833.pdf?arnumber=7580833],
: [http://dx.doi.org/10.1109/isc2.2016.7580833 http://dx.doi.org/10.1109/isc2.2016.7580833]

* [https://ieeexplore.ieee.org/document/7580833 https://ieeexplore.ieee.org/document/7580833],
: [https://dblp.uni-trier.de/db/conf/isc2/isc2016.html#BelliniNPV16 https://dblp.uni-trier.de/db/conf/isc2/isc2016.html#BelliniNPV16],
: [https://flore.unifi.it/handle/2158/1088813 https://flore.unifi.it/handle/2158/1088813],
: [http://doi.org/10.1109/ISC2.2016.7580833 http://doi.org/10.1109/ISC2.2016.7580833],
: [http://ieeexplore.ieee.org/document/7580833 http://ieeexplore.ieee.org/document/7580833],
: [https://doi.org/10.1109/ISC2.2016.7580833 https://doi.org/10.1109/ISC2.2016.7580833],
: [https://academic.microsoft.com/#/detail/2528169566 https://academic.microsoft.com/#/detail/2528169566]

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Nesi et al 2016a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 945214558 to Nesi et al 2016a

Scipediacontent: Created page with " == Abstract == Today, managing critical infrastructure resilience in smart city is a challenge that can be undertaken by adopting a new class of smart tools, which are able..."