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Pregled bibliografske jedinice broj: 813910

Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models

Kovač-Andrić, Elvira; Sheta, Alaa; Faris, Hossam; Šrajer Gajdošik, Martina
Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models // Journal of Earth System Science, 125 (2016), 5; 997-1006 doi:10.1007/s12040-016-0705-y (međunarodna recenzija, članak, znanstveni)

CROSBI ID: 813910 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models

Autori
Kovač-Andrić, Elvira ; Sheta, Alaa ; Faris, Hossam ; Šrajer Gajdošik, Martina

Izvornik
Journal of Earth System Science (0253-4126) 125 (2016), 5; 997-1006

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Ozone ; PM10 ; rural and urban area ; prediction models ; Artificial Neural Networks.

Sažetak
Ozone is one of the most significant secondary pollutants with numerous negative effects on human health and environment including plants and vegetation. Therefore, more effort is made recently by governments and associations to predict ozone concentrations which could help in establishing better plans and regulation for environment protection. In this study, we use two Artificial Neural Network based approaches (MPL and RBF) to develop, for the first time, accurate ozone prediction models for one urban and one rural area in the Eastern part of Croatia. The evaluation of actual against the predicted ozone concentrations revealed that MLP and RBF models are very competitive for the training and testing data in the case of Kopački Rit area whereas in the case of Osijek city, MLP shows better evaluation results with 9% improvement in the correlation coefficient. Furthermore, subsequent feature selection process has improved the prediction power of RBF network.

Izvorni jezik
Engleski

Znanstvena područja
Kemija



POVEZANOST RADA

Ustanove:
Sveučilište u Osijeku - Odjel za kemiju

Profili:

Avatar Url Martina Srajer Gajdosik (autor)

Avatar Url Elvira Kovač Andrić (autor)

Poveznice na cjeloviti tekst rada:

doi link.springer.com link.springer.com

Citiraj ovu publikaciju:

Kovač-Andrić, Elvira; Sheta, Alaa; Faris, Hossam; Šrajer Gajdošik, Martina
Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models // Journal of Earth System Science, 125 (2016), 5; 997-1006 doi:10.1007/s12040-016-0705-y (međunarodna recenzija, članak, znanstveni)
Kovač-Andrić, E., Sheta, A., Faris, H. & Šrajer Gajdošik, M. (2016) Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models. Journal of Earth System Science, 125 (5), 997-1006 doi:10.1007/s12040-016-0705-y.
@article{article, author = {Kova\v{c}-Andri\'{c}, Elvira and Sheta, Alaa and Faris, Hossam and \v{S}rajer Gajdo\v{s}ik, Martina}, year = {2016}, pages = {997-1006}, DOI = {10.1007/s12040-016-0705-y}, keywords = {Ozone, PM10, rural and urban area, prediction models, Artificial Neural Networks.}, journal = {Journal of Earth System Science}, doi = {10.1007/s12040-016-0705-y}, volume = {125}, number = {5}, issn = {0253-4126}, title = {Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models}, keyword = {Ozone, PM10, rural and urban area, prediction models, Artificial Neural Networks.} }
@article{article, author = {Kova\v{c}-Andri\'{c}, Elvira and Sheta, Alaa and Faris, Hossam and \v{S}rajer Gajdo\v{s}ik, Martina}, year = {2016}, pages = {997-1006}, DOI = {10.1007/s12040-016-0705-y}, keywords = {Ozone, PM10, rural and urban area, prediction models, Artificial Neural Networks.}, journal = {Journal of Earth System Science}, doi = {10.1007/s12040-016-0705-y}, volume = {125}, number = {5}, issn = {0253-4126}, title = {Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models}, keyword = {Ozone, PM10, rural and urban area, prediction models, Artificial Neural Networks.} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus

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