Copper Price Time Series Forecasting by Means of Generalized Regression Neural Networks with Optimized Predictor Variables

dc.contributor.author	Fidalgo Valverde, Gregorio
dc.contributor.author	Krzemien, A.
dc.contributor.author	Riesgo Fernández, Pedro
dc.contributor.author	Iglesias Rodríguez, Francisco Javier
dc.contributor.author	Suárez Sánchez, Ana
dc.date.accessioned	2021-06-01T09:43:48Z
dc.date.available	2021-06-01T09:43:48Z
dc.date.issued	2021
dc.identifier.isbn	9783030578015
dc.identifier.issn	2194-5357
dc.identifier.uri	http://hdl.handle.net/10651/58878
dc.description	International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO) (15th. 2020. Burgos, Spain)
dc.format.extent	p. 681-690
dc.language.iso	eng
dc.relation.ispartof	15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)
dc.relation.ispartofseries	Advances in Intelligent Systems and Computing; 1268
dc.rights	© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091268878&doi=10.1007%2f978-3-030-57802-2_65&partnerID=40&md5=e781c1ad53742b6f432d1aed33bf9176
dc.title	Copper Price Time Series Forecasting by Means of Generalized Regression Neural Networks with Optimized Predictor Variables
dc.type	conference output	spa
dc.identifier.doi	10.1007/978-3-030-57802-2_65
dc.relation.publisherversion	http://dx.doi.org/10.1007/978-3-030-57802-2_65

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