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A Rigorous Inter-Comparison of Ground-Level Ozone Predictions

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    0404801 - UIVT-O 20030021 RIV GB eng J - Journal Article
    Schlink, U. - Dorling, S.R. - Pelikán, Emil - Nunnari, G. - Cawley, C. - Junninen, H. - Greig, A. - Foxall, R. - Eben, Kryštof - Chatterton, T. - Vondráček, Jiří - Richter, M. - Dostál, Michal - Bertucco, L. - Kolehmainen, M. - Doyle, M.
    A Rigorous Inter-Comparison of Ground-Level Ozone Predictions.
    Atmospheric Environment. Roč. 37, - (2003), s. 3237-3253. ISSN 1352-2310. E-ISSN 1873-2844
    Grant - others:APPETISE(XE) IST-1999-11764
    Institutional research plan: AV0Z1030915
    Keywords : statistical methods * air polution * neural networks
    Subject RIV: BB - Applied Statistics, Operational Research
    Impact factor: 2.338, year: 2003

    Novel statistical approaches to prediction have recently been shown to perform well in several scientific fields but have not, until now, been comprehensively evaluated for predicting air pollution. In this paper we report on a model inter-comparison exercise in which 15 different statistical techniques for ozone forecasting were applied to ten data sets representing different meteorological and emission conditions throughout Europe.We also attempt to compare the performance of the statistical techniques...
    Permanent Link: http://hdl.handle.net/11104/0125034

     
     

Number of the records: 1  

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