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Income prediction in the agrarian sector using product unit neural networks

dc.contributor.authorGarcía Alonso, Carlos 
dc.contributor.authorTorres Jiménez, Mercedes 
dc.contributor.authorHervas Martínez, César
dc.date.accessioned2019-02-04T15:19:13Z
dc.date.available2019-02-04T15:19:13Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/20.500.12412/1032
dc.description.abstractEuropean Union financial subsidies in the agrarian sector are directly related to maintaining a sustainable farm income, so its determination using, for example, the farm gross margin is a basic element in agrarian programs for sustainable development. Using this tool, it is possible the identification of the agrarian structures that need financial support and to what extent it is needed. However, the process of farm gross margin determination is complicated and expensive because it is necessary to find the value of all the inputs consumed and outputs produced.es
dc.language.isoenges
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleIncome prediction in the agrarian sector using product unit neural networkses
dc.typearticlees
dc.identifier.doi10.1016/j.ejor.2009.09.033
dc.issue.number2es
dc.journal.titleEuropean Journal Of Operational Researches
dc.page.initial355es
dc.page.final365es
dc.rights.accessRightsopenAccesses
dc.subject.keywordneural networkses
dc.subject.keywordOR in agriculturees
dc.subject.keywordproduct-unit modelses
dc.subject.keywordregressiones
dc.volume.number204es


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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