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Particle swarm grammatical evolution for energy demand estimation

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Particle swarm grammatical evolution for energy demand estimation

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Nombre: Martínez-Rodrígue ...
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dc.contributor.author Martínez-Rodríguez, David es_ES
dc.contributor.author Colmenar, J. Manuel es_ES
dc.contributor.author Hidalgo, J. Ignacio es_ES
dc.contributor.author Villanueva Micó, Rafael Jacinto es_ES
dc.contributor.author Salcedo-Sanz, Sancho es_ES
dc.date.accessioned 2021-02-11T04:32:10Z
dc.date.available 2021-02-11T04:32:10Z
dc.date.issued 2020-04 es_ES
dc.identifier.uri http://hdl.handle.net/10251/161045
dc.description.abstract [EN] Grammatical Swarm is a search and optimization algorithm that belongs to the more general Grammatical Evolution family, which works with a set of solutions called individuals or particles. It uses the Particle Swarm Optimization algorithm as the search engine in the evolution of solutions. In this paper, we present a Grammatical Swarm algorithm for total energy demand estimation in a country from macroeconomic variables. Each particle in the Grammatical Swarm encodes a different model for energy demand estimation, which will be decoded by a predefined grammar. The parameters of the model are also optimized by the proposed algorithm, in such a way that the model is adjusted to a training set of real energy demand data, selecting the more appropriate variables to appear in the model. We analyze the performance of the Grammatical Swarm evolution in two real problems of one-year ahead energy demand estimation in Spain and France. The proposal is compared with previous approaches with competitive results. es_ES
dc.description.sponsorship Spanish Ministerial Commission of Science and Technology (MICYT), Grant/Award Number: TIN2017-85887-C2-2-P; Ministerio de Ciencia, Innovacion y Universidades, Grant/Award Number: PGC2018-095322-B-C22 and RTI2018-095180-B-I00; Comunidad de Madrid y Fondos Estructurales de la Union Europea, Grant/Award Number: S2018/TCS-4566 and Y2018/NMT-4668; GenObIA-CM, Grant/Award Number: S2017/BMD-3773; Ministerio de Economia, Industria y Competitividad, Grant/Award Number: MTM2017-89664-P es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons Ltd es_ES
dc.relation.ispartof Energy Science & Engineering es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Energy prediction models es_ES
dc.subject Grammatical swarm evolution es_ES
dc.subject Macroeconomic variables es_ES
dc.subject Total energy demand es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Particle swarm grammatical evolution for energy demand estimation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/ese3.568 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095180-B-I00/ES/SISTEMA ADAPTATIVO BIOINSPIRADO PARA EL CONTROL GLUCEMICO BASADO EN SENSORES Y ACCESORIOS INTELIGENTES/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CAM//Y2018%2FNMT- 4668/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CAM//S2017%2FBMD-3773/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-85887-C2-2-P/ES/NUEVOS ALGORITMOS HIBRIDOS DE INSPIRACION NATURAL PARA PROBLEMAS DE CLASIFICACION ORDINAL Y PREDICCION/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095322-B-C22/ES/METAHEURISTICAS EFICIENTES PARA LA OPTIMIZACION EN GRAFOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/CAM//S2018%2FTCS-4566/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària es_ES
dc.description.bibliographicCitation Martínez-Rodríguez, D.; Colmenar, JM.; Hidalgo, JI.; Villanueva Micó, RJ.; Salcedo-Sanz, S. (2020). Particle swarm grammatical evolution for energy demand estimation. Energy Science & Engineering. 8(4):1068-1079. https://doi.org/10.1002/ese3.568 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/ese3.568 es_ES
dc.description.upvformatpinicio 1068 es_ES
dc.description.upvformatpfin 1079 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 8 es_ES
dc.description.issue 4 es_ES
dc.identifier.eissn 2050-0505 es_ES
dc.relation.pasarela S\402083 es_ES
dc.contributor.funder Comunidad de Madrid es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
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