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dc.contributor.authorCampos Ibáñez, Luis Miguel 
dc.contributor.authorGonzález Muñoz, Antonio 
dc.date.accessioned2022-11-10T08:10:09Z
dc.date.available2022-11-10T08:10:09Z
dc.date.issued1993-09
dc.identifier.citationLuis M. de Campos, Antonio González, A fuzzy inference model based on an uncertainty forward propagation approach, International Journal of Approximate Reasoning, Volume 9, Issue 2, 1993, Pages 139-164, ISSN 0888-613X, [https://doi.org/10.1016/0888-613X(93)90017-8]es_ES
dc.identifier.urihttps://hdl.handle.net/10481/77867
dc.description.abstractThe management of uncertainty and imprecision is becoming more and more important in knowledge-based systems. Fuzzy logic provides a systematic basis for representing and inferring with this kind of knowledge. This paper describes an approach for fuzzy inference based on an uncertainty forward propagation method and a change in the granularity of the elements involved. The proposed model is able to handle very general kinds of facts and rules, and it also verifies the most usual properties required by a fuzzy inference model.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectFuzzy logic es_ES
dc.subjectFuzzy inferencees_ES
dc.subjectUncertainty managementes_ES
dc.subjectUpper and lower probabilitieses_ES
dc.subjectInteligencia artificial es_ES
dc.subjectArtificial intelligence es_ES
dc.titleA Fuzzy Inference Model Based on an Uncertainty Forward Propagation Approaches_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/0888-613X(93)90017-8
dc.type.hasVersionVoRes_ES


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