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Volumn 23, Issue 4, 2006, Pages 603-609

Short-time forecasting of atmospheric NOX concentration by neural networks

Author keywords

Artificial neural networks; Modeling; NOx concentration; Short time forecasting; Time series analysis

Indexed keywords

ATMOSPHERIC CHEMISTRY; IMPURITIES; MATHEMATICAL MODELS; NEURAL NETWORKS; TIME SERIES ANALYSIS;

EID: 33747151045     PISSN: 10928758     EISSN: None     Source Type: Journal    
DOI: 10.1089/ees.2006.23.603     Document Type: Article
Times cited : (11)

References (7)
  • 1
    • 0036224943 scopus 로고    scopus 로고
    • Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks
    • ABDUL-WAHAB, S.A., and AL-ALAWI, S.M. (2002). Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks. Environ. Model. Software 17, 219.
    • (2002) Environ. Model. Software , vol.17 , pp. 219
    • Abdul-Wahab, S.A.1    Al-Alawi, S.M.2
  • 2
    • 0032146239 scopus 로고    scopus 로고
    • Artificial neural networks (the multilayer perceptron) - A review of applications in the atmospheric sciences
    • GARDNER, M.W., and DORLING, S.R. (1998). Artificial neural networks (the multilayer perceptron)-A review of applications in the atmospheric sciences. Atmos. Environ. 32, 2627.
    • (1998) Atmos. Environ. , vol.32 , pp. 2627
    • Gardner, M.W.1    Dorling, S.R.2
  • 3
    • 0032768619 scopus 로고    scopus 로고
    • A comparison of modeling nonlinear systems with artificial neural networks and partial least squares
    • HADJIISKI, L., GELADI, P., and HOPKE, P. (1999). A comparison of modeling nonlinear systems with artificial neural networks and partial least squares. Chemom. Intell. Lab. Syst. 49, 91.
    • (1999) Chemom. Intell. Lab. Syst. , vol.49 , pp. 91
    • Hadjiiski, L.1    Geladi, P.2    Hopke, P.3
  • 4
    • 0033151368 scopus 로고    scopus 로고
    • Requirements for the completeness of ambient air quality data sets with respect to derived parameters
    • HAUCK, H., KROMP-KOLB, H., and PETZ, E. (1999). Requirements for the completeness of ambient air quality data sets with respect to derived parameters. Atmos. Environ. 33, 2059.
    • (1999) Atmos. Environ. , vol.33 , pp. 2059
    • Hauck, H.1    Kromp-Kolb, H.2    Petz, E.3
  • 5
    • 33747172720 scopus 로고    scopus 로고
    • Regression modelling of ground level ozone concentration
    • L. Pawłowski, M.R. Dudzińska, and A. Pawłowski, Eds. New York: Kluwer Academic/Plenum Publishers
    • HOFFMAN, S. (2003). Regression modelling of ground level ozone concentration. In L. Pawłowski, M.R. Dudzińska, and A. Pawłowski, Eds., Environmental Egineering Studies. Polish Research on the way to EU. New York: Kluwer Academic/Plenum Publishers, p. 53.
    • (2003) Environmental Egineering Studies. Polish Research on the Way to EU , pp. 53
    • Hoffman, S.1
  • 7
    • 0034739912 scopus 로고    scopus 로고
    • Neural networks and periodic components used in air quality forecasting
    • KOLEHMAINEN, M., MARTIKAINEN, H., and RUUSKANEN, J. (2001). Neural networks and periodic components used in air quality forecasting. Atmos. Environ. 35, 815.
    • (2001) Atmos. Environ. , vol.35 , pp. 815
    • Kolehmainen, M.1    Martikainen, H.2    Ruuskanen, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.