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Application of radial basis functions compared to neural networks to predict air pollution

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Application of radial basis functions compared to neural networks to predict air pollution

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dc.contributor.author Capilla, Carmen es_ES
dc.date.accessioned 2016-05-11T07:31:54Z
dc.date.available 2016-05-11T07:31:54Z
dc.date.issued 2015
dc.identifier.issn 1746-448X
dc.identifier.uri http://hdl.handle.net/10251/63886
dc.description.abstract This paper studies the application of radial basis functions to predict nitrogen oxides 24 hours in advance. The forecast interval was chosen for practical regulatory reasons. The two study areas are in Valencia (Spain), where these pollutants have reached critical levels, and there has been a significant connection between them and several health problems. The models use as inputs hourly nitrogen oxides concentrations, traffic, meteorological data, and periodic components (sine and cosine terms for the daily and weekly cycles). In one monitoring station the most accurate nitric oxide predictions were obtained when the radial basis function model included as inputs all these variables. In this site the forecast evaluation criteria gave better results for nitrogen dioxide prediction than for nitric oxide. In the other monitoring station, better predictions were obtained for nitric oxides than for nitrogen dioxide. There were differences in the forecasts accuracy between sites. The results are compared with the forecasts obtained with multilayer perceptron neural networks. Nitrogen dioxide predictions were more accurate with the multilayer perceptron approach at one of the sites. es_ES
dc.language Inglés es_ES
dc.publisher WIT Press es_ES
dc.relation.ispartof WIT Transactions on Ecology and the Environment es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Urban air quality es_ES
dc.subject Nitrogen oxides es_ES
dc.subject Neural networks es_ES
dc.subject Radial basis functions es_ES
dc.subject Multiplayer perceptron es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Application of radial basis functions compared to neural networks to predict air pollution es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.2495/AIR150051
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Capilla, C. (2015). Application of radial basis functions compared to neural networks to predict air pollution. WIT Transactions on Ecology and the Environment. 198:41-50. doi:10.2495/AIR150051 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.2495/AIR150041 es_ES
dc.description.upvformatpinicio 41 es_ES
dc.description.upvformatpfin 50 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 198 es_ES
dc.relation.senia 290786 es_ES
dc.identifier.eissn 1743-3541


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