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dc.contributor.author | Herrero Cosío, Álvaro | |
dc.contributor.author | Sáiz Bárcena, Lourdes | |
dc.contributor.author | Corchado Rodríguez, Emilio Santiago | |
dc.date.accessioned | 2017-09-06T09:14:57Z | |
dc.date.available | 2017-09-06T09:14:57Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Trends in Practical Applications of Agents and Multiagent Systems Advances in Intelligent and Soft Computing. Advances in Intelligent and Soft Computing. Volumen 71, pp. 721-729. | |
dc.identifier.isbn | 978-3-642-12432-7 (Print) / 978-3-642-12433-4 (Online) | |
dc.identifier.issn | 1867-5662 (Print) / 1867-5670 (Online) | |
dc.identifier.uri | http://hdl.handle.net/10366/134931 | |
dc.description.abstract | It has been proven that Artificial Intelligence, in general, and Artificial Neural Networks, in particular, can be successfully applied to problems in the field of Knowledge Management (KM). One such problem is the identification and assessment of a company’s KM status. Nowadays the importance of KM to organisational survival and for the maintenance of competitive strength is widely acknowledged. Several connectionist models for the assessment and analysis of KM status are proposed and applied in this work. These models account for the specific features of a company in the Energy sector/Power sector: a dynamic, essential service and one of the basic pillars that supports the so-called “welfare state”, constituting an established strategic sector in any globalized economy. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.publisher | Springer Science + Business Media | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Unported | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ | |
dc.subject | Computer Science | |
dc.title | Assessing Knowledge Management in the Power Sector through a Connectionist Model | |
dc.type | info:eu-repo/semantics/article | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
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