2026-09-17T06:23:05Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1344162025-04-30T20:37:24Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243

Borrajo Diz, María Lourdes Corchado Rodríguez, Juan Manuel Corchado Rodríguez, Emilio Santiago Pellicer Figueras, María A. Bajo Pérez, Javier 2017-09-05T11:02:02Z 2017-09-05T11:02:02Z 2010 Information Sciences. Volumen 180 (6), pp. 911-927. Elsevier BV. 0020-0255 (Print) http://hdl.handle.net/10366/134416 Small to medium sized companies require a business control mechanism in order to monitor their modus operandi and analyse whether they are achieving their goals. A tool for the decision support process was developed based on a multi-agent system that incorporates a case-based reasoning system and automates the business control process. The case-based reasoning system automates the organization of cases and the retrieval stage by means of a Maximum Likelihood Hebbian Learning-based method, an extension of the Principal Component Analysis which groups similar cases by automatically identifying clusters in a data set in an unsupervised mode. The multi-agent system was tested with 22 small and medium sized companies in the textile sector located in the northwest of Spain during 29 months, and the results obtained have been very satisfactory. application/pdf en Elsevier BV Attribution-NonCommercial-NoDerivs 3.0 Unported https://creativecommons.org/licenses/by-nc-nd/3.0/ info:eu-repo/semantics/openAccess Computer Science Multi-agent neural business control system info:eu-repo/semantics/article