메뉴 건너뛰기




Volumn , Issue , 2015, Pages 176-181

A comprehensive evaluation of air pollution prediction improvement by a machine learning method

Author keywords

air pollutation prediction; air quality index prediction; combined method; machine learning

Indexed keywords

AIR POLLUTION; AIR QUALITY; ARTIFICIAL INTELLIGENCE; FORECASTING; INFORMATION SCIENCE; POLLUTION;

EID: 84963594723     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SOLI.2015.7367615     Document Type: Conference Paper
Times cited : (78)

References (20)
  • 1
    • 0019992510 scopus 로고
    • A mathematical model for air pollution forecast and alarm in an urban area
    • Finzi, G., Tebaldi, G., A mathematical model for air pollution forecast and alarm in an urban area. Atmospheric Environment 16, 2055-2059. 1982.
    • (1982) Atmospheric Environment , vol.16 , pp. 2055-2059
    • Finzi, G.1    Tebaldi, G.2
  • 4
    • 84963528935 scopus 로고    scopus 로고
    • Hybrid model for urban air pollution forecasting: A stochastic spatio-temporal approach
    • Ana Russo, Hybrid Model for Urban Air Pollution Forecasting: A Stochastic Spatio-Temporal Approach. Math Geosci, 2013.
    • (2013) Math Geosci
    • Russo, A.1
  • 5
    • 33749247555 scopus 로고    scopus 로고
    • Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations
    • Sousa, S. I. V., Martins, F. G., Alvim, Ferraz, M. C. M., Pereira, M. C. Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations. Environmental Modelling and Software 22, 97-103. 2007
    • (2007) Environmental Modelling and Software , vol.22 , pp. 97-103
    • Sousa, S.I.V.1    Martins, F.G.2    Alvim Ferraz, M.C.M.3    Pereira, M.C.4
  • 6
    • 84923017379 scopus 로고    scopus 로고
    • Artificial neural networks forecasting of PM2. 5 polluting using air mass trajectory based geographic model and wavelet transformation
    • Xiao Feng, QiLi, et al, "Artificial neural networks forecasting of PM2. 5 polluting using air mass trajectory based geographic model and wavelet transformation," Atmospheric Environment, pp. 118-128, 2015
    • (2015) Atmospheric Environment , pp. 118-128
    • Feng, X.1    Li, Q.2
  • 7
    • 33748783344 scopus 로고    scopus 로고
    • Ground-level ozone prediction using multilayer perceptron trained with an innovative hybrid approach
    • Wang, D., Lu, W. Z. 2006. Ground-level ozone prediction using multilayer perceptron trained with an innovative hybrid approach. Ecological Modelling 198, 332-340.
    • (2006) Ecological Modelling , vol.198 , pp. 332-340
    • Wang, D.1    Lu, W.Z.2
  • 9
    • 0012772509 scopus 로고    scopus 로고
    • ENVIRON International Corporation ENVIRON International Corporation, Novato, California June Available at
    • ENVIRON International Corporation. User's Guide Comprehensive Air Quality Model with Extensions (CAMx) Version 4. 00. ENVIRON International Corporation, Novato, California. June 2003. Available at www. camx. com.
    • (2003) User's Guide Comprehensive Air Quality Model with Extensions (CAMx) Version 4. 00
  • 11
    • 84922676197 scopus 로고    scopus 로고
    • International Journal of Innovation and Scientific Research Nov.
    • International Journal of Innovation and Scientific Research ISSN 2351-8014 Vol. 11 No. 2 Nov. 2014, pp. 237-247© 2014 Innovative Space of Scientific Research Journals http://www. ijisr. issr-journals. org/
    • (2014) 2014 Innovative Space of Scientific Research Journals , vol.11 , Issue.2 , pp. 237-247
  • 12
    • 0343907347 scopus 로고    scopus 로고
    • Regression modelling of hourly NOX and NO2 concentrations in urban air in London
    • Shi, J. P., Harrison, R. M. Regression modelling of hourly NOX and NO2 concentrations in urban air in London. Atmospheric Environment 31, 4081-4094., 1997
    • (1997) Atmospheric Environment , vol.31 , pp. 4081-4094
    • Shi, J.P.1    Harrison, R.M.2
  • 13
    • 0027610496 scopus 로고
    • A neural network based method for short term predictions of ambient SO2 concentrations in highly polluted industrial areas of complex terrain
    • Boznar, M., Lesjak, M., Mlakar, P. A neural network based method for short term predictions of ambient SO2 concentrations in highly polluted industrial areas of complex terrain. Atmospheric Environment Part B Urban Atmosphere 27, 221-230., 1993
    • (1993) Atmospheric Environment Part B Urban Atmosphere , vol.27 , pp. 221-230
    • Boznar, M.1    Lesjak, M.2    Mlakar, P.3
  • 14
  • 16
    • 84963601982 scopus 로고    scopus 로고
    • https://www2. acom. ucar. edu/wrf-chem
  • 18
    • 84898978212 scopus 로고    scopus 로고
    • Boosting algorithms as gradient descent (PDF)
    • S. A. Solla and T. K. Leen and K. Müller MIT Press
    • Mason, L. ; Baxter, J. ; Bartlett, P. L. ; Frean, Marcus. "Boosting Algorithms as Gradient Descent" (PDF). In S. A. Solla and T. K. Leen and K. Müller. Advances in Neural Information Processing Systems 12. MIT Press. pp. 512-518,1999
    • (1999) Advances in Neural Information Processing Systems , vol.12 , pp. 512-518
    • Mason, L.1    Baxter, J.2    Bartlett, P.L.3    Marcus, F.4
  • 20
    • 33744584654 scopus 로고
    • Induction of decision trees
    • Kluwer Academic Publishers
    • Quinlan, J. R. Induction of Decision Trees. Machine Learning 1: 81-106, Kluwer Academic Publishers, 1986
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, J.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.