Mathematical Analysis of Uncertainty

dc.contributor.author	Garrido, Angel
dc.date.accessioned	2016-01-21T10:10:37Z
dc.date.available	2016-01-21T10:10:37Z
dc.date.issued	2008
dc.identifier.uri	http://10.11.10.50/xmlui/handle/123456789/3919
dc.description	The Annals of "Dunarea de Jos" University of Galati	en_US
dc.description.abstract	Classical Logic showed early its insufficiencies for solving AI problems. The introduction of Fuzzy Logic aims at this problem. There have been research in the conventional Rough direction alone or in the Fuzzy direction alone, and more recently, attempts to combine both into Fuzzy Rough Sets or Rough Fuzzy Sets. We analyse some new and powerful tools in the study of Uncertainty, as the Probabilistic Graphical Models, Chain Graphs, Bayesian Networks, and Markov Networks, integrating our knowledge of graphs and probability.	en_US
dc.language.iso	en	en_US
dc.publisher	"Dunarea de Jos" University of Galati	en_US
dc.subject	Fuzzy Sets	en_US
dc.subject	Rough Sets	en_US
dc.subject	Fuzzy Analysis	en_US
dc.subject	Knowledge Representation	en_US
dc.subject	Artificial Intelligence	en_US
dc.title	Mathematical Analysis of Uncertainty	en_US
dc.type	Article	en_US