A new predictive model for the cyanotoxin content from experimental cyanobacteria concentrations in a reservoir based on the ABC optimized support vector machine approach: A case study in Northern Spain

dc.contributor.author	García Nieto, Paulino José
dc.contributor.author	Alonso Fernández, José Ramón
dc.contributor.author	García Gonzalo, María Esperanza
dc.contributor.author	Díaz Muñiz, C.
dc.contributor.author	Mayo Bayón, Ricardo
dc.contributor.author	González Suárez, Víctor Manuel
dc.date.accessioned	2016-05-06T09:27:43Z
dc.date.available	2016-05-06T09:27:43Z
dc.date.issued	2015
dc.identifier.citation	Ecological Informatics, 30, p. 49-59 (2015); doi:10.1016/j.ecoinf.2015.09.010
dc.identifier.issn	1574-9541
dc.identifier.uri	http://hdl.handle.net/10651/36853
dc.format.extent	p. 49-59
dc.language.iso	eng
dc.relation.ispartof	Ecological Informatics
dc.rights	©,
dc.source	Scopus
dc.source.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-84955577950&partnerID=40&md5=ec214710ae3242395a03b15af50b97cf
dc.title	A new predictive model for the cyanotoxin content from experimental cyanobacteria concentrations in a reservoir based on the ABC optimized support vector machine approach: A case study in Northern Spain	eng
dc.type	journal article
dc.identifier.doi	10.1016/j.ecoinf.2015.09.010
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.ecoinf.2015.09.010

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