dc.creator | Martínez Ballesteros, María del Mar | es |
dc.creator | Salcedo Sanz, S. | es |
dc.creator | Riquelme Santos, José Cristóbal | es |
dc.creator | Casanova Mateo, C. | es |
dc.creator | Camacho, J. L. | es |
dc.date.accessioned | 2022-04-26T09:33:55Z | |
dc.date.available | 2022-04-26T09:33:55Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Martínez Ballesteros, M.d.M., Salcedo Sanz, S., Riquelme Santos, J.C., Casanova Mateo, C. y Camacho, J.L. (2011). Evolutionary association rules for total ozone content modeling from satellite observations. Chemometrics and Intelligent Laboratory Systems, 109 (2), 217-227. | |
dc.identifier.issn | 0169-7439 | es |
dc.identifier.uri | https://hdl.handle.net/11441/132621 | |
dc.description.abstract | In this paper we propose an evolutionary method of association rules discovery (EQAR, Evolutionary Quan titative Association Rules) that extends a recently published algorithm by the authors and we describe its ap plication to a problem of Total Ozone Content (TOC) modeling in the Iberian Peninsula. We use TOC data from
the Total Ozone Mapping Spectrometer (TOMS) on board the NASA Nimbus-7 satellite measured at three lo cations (Lisbon, Madrid and Murcia) of the Iberian Peninsula. As prediction variables for the association rules
we consider several meteorological variables, such as Outgoing Long-wave Radiation (OLR), Temperature at
50 hPa level, Tropopause height, and wind vertical velocity component at 200 hPa. We show that the best as sociation rules obtained by EQAR are able to accurate modeling the TOC data in the three locations consid ered, providing results which agree to previous works in the literature | es |
dc.format | application/pdf | es |
dc.format.extent | 11 | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Chemometrics and Intelligent Laboratory Systems, 109 (2), 217-227. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Association Rules | es |
dc.subject | Evolutionary algorithms | es |
dc.subject | Total Ozone Content (TOC) | es |
dc.subject | Satellite data | es |
dc.title | Evolutionary association rules for total ozone content modeling from satellite observations | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0169743911002012 | es |
dc.identifier.doi | 10.1016/j.chemolab.2011.09.011 | es |
dc.contributor.group | Universidad de Sevilla. TIC-254: Data Science and Big Data Lab | es |
dc.journaltitle | Chemometrics and Intelligent Laboratory Systems | es |
dc.publication.volumen | 109 | es |
dc.publication.issue | 2 | es |
dc.publication.initialPage | 217 | es |
dc.publication.endPage | 227 | es |
dc.identifier.sisius | 20101556 | es |