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dc.contributor.authorFernández Canelas, Jesús Ángel
dc.contributor.authorMartín Martín, Quintín 
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.date.accessioned2017-09-05T10:59:47Z
dc.date.available2017-09-05T10:59:47Z
dc.date.issued2013
dc.identifier.citationApplied Computational Intelligence and Soft Computing. Volumen 2013, pp. 1-23. Hindawi Publishing Corporation.
dc.identifier.issn1687-9724 (Print) / 1687-9732 (Online)
dc.identifier.urihttp://hdl.handle.net/10366/134333
dc.description.abstractThe objective of this paper is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility and quality of the Suppliers Selection Process based on Artificial Intelligence and Argumentation Theory knowledge and techniques. The present SOX Law, in effect nowadays, was created to improve financial government control over US companies. This law is a factor standard out United States due to several factors like present globalization, expansion of US companies, or key influence of US stock exchange markets worldwide. This paper constitutes a novel approach to this kind of problems due to following elements: (1) it has an optimized structure to look for the solution, (2) it has a dynamic learning method to handle court and control gonvernment bodies decisions, (3) it uses fuzzy knowledge to improve its performance, and (4) it uses its past accumulated experience to let the system evolve far beyond its initial state.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherHindawi Publishing Corporation
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleArgumentative SOX Compliant and Quality Decision Support Intelligent Expert System over the Suppliers Selection Process
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
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