Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean

This paper presents a multiagent system developed to predict the behaviour of the Atlantic Ocean in relation to the sinks/sources of CO2. The heart of the multiagent system is an intelligent agent capable of automatically making predictions about the flux of CO2 in the North Atlantic ocean. The mult...

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Main Authors: Corchado Rodríguez, Juan Manuel, Bajo Pérez, Javier, Alonso, Vidal
Format: Article in Journal/Newspaper
Language:English
Published: Institute of Electrical & Electronics Engineers (IEEE) 2008
Subjects:
Computer Science
North Atlantic
Online Access:http://hdl.handle.net/10366/134440
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record_format openpolar
spelling ftunivsalamanca:oai:gredos.usal.es:10366/134440 2024-06-23T07:54:54+00:00 Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean Corchado Rodríguez, Juan Manuel Bajo Pérez, Javier Alonso, Vidal 2008 application/pdf http://hdl.handle.net/10366/134440 en eng Institute of Electrical & Electronics Engineers (IEEE) IEEE Latin America Transactions. Volumen 6 (6), pp. 505-510. Institute of Electrical & Electronics Engineers (IEEE). 1548-0992 (Print) http://hdl.handle.net/10366/134440 Attribution-NonCommercial-NoDerivs 3.0 Unported https://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Computer Science info:eu-repo/semantics/article 2008 ftunivsalamanca 2024-06-11T14:23:20Z This paper presents a multiagent system developed to predict the behaviour of the Atlantic Ocean in relation to the sinks/sources of CO2. The heart of the multiagent system is an intelligent agent capable of automatically making predictions about the flux of CO2 in the North Atlantic ocean. The multiagent system has been tested in simulation conditions and this work presents the preliminary obtained results. Article in Journal/Newspaper North Atlantic Universidad de Salamanca: Gredos (Gestión del Repositorio Documental de la Universidad de Salamanca)
institution Open Polar
collection Universidad de Salamanca: Gredos (Gestión del Repositorio Documental de la Universidad de Salamanca)
op_collection_id ftunivsalamanca
language English
topic Computer Science
spellingShingle Computer Science
Corchado Rodríguez, Juan Manuel
Bajo Pérez, Javier
Alonso, Vidal
Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean
topic_facet Computer Science
description This paper presents a multiagent system developed to predict the behaviour of the Atlantic Ocean in relation to the sinks/sources of CO2. The heart of the multiagent system is an intelligent agent capable of automatically making predictions about the flux of CO2 in the North Atlantic ocean. The multiagent system has been tested in simulation conditions and this work presents the preliminary obtained results.
format Article in Journal/Newspaper
author Corchado Rodríguez, Juan Manuel
Bajo Pérez, Javier
Alonso, Vidal
author_facet Corchado Rodríguez, Juan Manuel
Bajo Pérez, Javier
Alonso, Vidal
author_sort Corchado Rodríguez, Juan Manuel
title Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean
title_short Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean
title_full Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean
title_fullStr Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean
title_full_unstemmed Multiagent System For Predicting The Co2 Exchange In The North Atlantic Ocean
title_sort multiagent system for predicting the co2 exchange in the north atlantic ocean
publisher Institute of Electrical & Electronics Engineers (IEEE)
publishDate 2008
url http://hdl.handle.net/10366/134440
genre North Atlantic
genre_facet North Atlantic
op_relation IEEE Latin America Transactions. Volumen 6 (6), pp. 505-510. Institute of Electrical & Electronics Engineers (IEEE).
1548-0992 (Print)
http://hdl.handle.net/10366/134440
op_rights Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
_version_ 1802647241054224384

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