Scipediacontent: Scipediacontent moved page Draft Content 817941583 to Duviella et al 2013a

2021-02-02T04:35:48Z

Scipediacontent moved page Draft Content 817941583 to Duviella et al 2013a

Scipediacontent: Created page with " == Abstract == In this paper, an adaptive and predictive control architecture is proposed to improve the management of inland navigation networks in a global change context...."

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Created page with " == Abstract == In this paper, an adaptive and predictive control architecture is proposed to improve the management of inland navigation networks in a global change context...."

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== Abstract ==

In this paper, an adaptive and predictive control architecture is proposed to improve the management of inland navigation networks in a global change context. This architecture aims at ensuring the seaworthiness conditions of inland navigation networks, and to improve the efficiency of the water resource management. It is based on supervision and prognosis modules which allow the estimation of the current state of the network, and the forecasting of the extreme event occurrence. According to these indicators and to the management constraints and objectives, control strategies of the inland navigation networks will be adapted to limit the impacts of the extreme events. To achieve this aim, three challenges are considered and discussed in this paper. The first one consists in proposing an accurate modeling approach of navigation reaches which are characterized by large scale, nonlinearities, time delays, unknown inputs and outputs, etc. The second one is to increase the knowledge about potentiality of extreme events, consequences of the climate change. The prediction of these events is rather complex due to their rarity, the spacio-temporal scale of the networks, etc. Finally, the third one is the pooling of the two first contributions, i.e. the model of the system and the knowledge about extreme events. Thus, the resilience of the system and the adaptation of the management strategies could be realized

Peer Reviewed

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_817941583-beopen4237-7770-document.pdf</pdf>

== Original document ==

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

* [http://hdl.handle.net/2117/22942 http://hdl.handle.net/2117/22942] under the license https://creativecommons.org/licenses/by-nc-nd

* [https://upcommons.upc.edu/bitstream/2117/22942/1/MIM_2013_Duviella_draft.pdf https://upcommons.upc.edu/bitstream/2117/22942/1/MIM_2013_Duviella_draft.pdf] under the license http://creativecommons.org/licenses/by-nc-nd/3.0/es/

* [https://api.elsevier.com/content/article/PII:S1474667016346249?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S1474667016346249?httpAccept=text/xml],
: [https://api.elsevier.com/content/article/PII:S1474667016346249?httpAccept=text/plain https://api.elsevier.com/content/article/PII:S1474667016346249?httpAccept=text/plain],
: [http://dx.doi.org/10.3182/20130619-3-ru-3018.00447 http://dx.doi.org/10.3182/20130619-3-ru-3018.00447] under the license cc-by-nc-nd

* [https://dblp.uni-trier.de/db/conf/mim/mim2013.html#DuviellaRBC13 https://dblp.uni-trier.de/db/conf/mim/mim2013.html#DuviellaRBC13],
: [http://upcommons.upc.edu/handle/2117/22942 http://upcommons.upc.edu/handle/2117/22942],
: [https://www.sciencedirect.com/science/article/pii/S1474667016346249 https://www.sciencedirect.com/science/article/pii/S1474667016346249],
: [https://upcommons.upc.edu/bitstream/2117/22942/1/MIM_2013_Duviella_draft.pdf https://upcommons.upc.edu/bitstream/2117/22942/1/MIM_2013_Duviella_draft.pdf],
: [https://academic.microsoft.com/#/detail/2005342133 https://academic.microsoft.com/#/detail/2005342133] under the license https://www.elsevier.com/tdm/userlicense/1.0/

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Scipediacontent: Scipediacontent moved page Draft Content 817941583 to Duviella et al 2013a

Scipediacontent: Created page with " == Abstract == In this paper, an adaptive and predictive control architecture is proposed to improve the management of inland navigation networks in a global change context...."