Show simple item record

dc.contributor.authorMaldonado González, Ana Devaki
dc.contributor.authorMorales Giraldo, María
dc.contributor.authorAguilera Aguilera, Pedro
dc.contributor.authorSalmerón Cerdán, Antonio
dc.date.accessioned2020-01-22T09:53:53Z
dc.date.available2020-01-22T09:53:53Z
dc.date.issued2020-01-19
dc.identifier.issn1099-4300
dc.identifier.urihttp://hdl.handle.net/10835/7684
dc.description.abstractSocio-ecological systems are recognized as complex adaptive systems whose multiple interactions might change as a response to external or internal changes. Due to its complexity, the behavior of the system is often uncertain. Bayesian networks provide a sound approach for handling complex domains endowed with uncertainty. The aim of this paper is to analyze the impact of the Bayesian network structure on the uncertainty of the model, expressed as the Shannon entropy. In particular, three strategies for model structure have been followed: naive Bayes (NB), tree augmented network (TAN) and network with unrestricted structure (GSS). Using these network structures, two experiments are carried out: (1) the impact of the Bayesian network structure on the entropy of the model is assessed and (2) the entropy of the posterior distribution of the class variable obtained from the different structures is compared. The results show that GSS constantly outperforms both NB and TAN when it comes to evaluating the uncertainty of the entire model. On the other hand, NB and TAN yielded lower entropy values of the posterior distribution of the class variable, which makes them preferable when the goal is to carry out predictions.es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBayesian networkses_ES
dc.subjectentropyes_ES
dc.subjectsocio-ecological systemes_ES
dc.titleAnalyzing Uncertainty in Complex Socio-Ecological Networkses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/1099-4300/22/1/123es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional