메뉴 건너뛰기




Volumn , Issue , 2009, Pages 1688-1692

Data-driven prediction model of indoor air quality by the preprocessed recurrent neural networks

Author keywords

Air quality prediction; Nonlinear modeling; Partial least squares (PLS); Predicted model; Recurrent neural networks (RNN)

Indexed keywords

AIR QUALITY PREDICTION; NONLINEAR MODELING; PARTIAL LEAST SQUARES; PARTIAL LEAST SQUARES (PLS); PREDICTED MODEL;

EID: 77951141165     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (16)

References (10)
  • 1
    • 77951139863 scopus 로고    scopus 로고
    • Evaluation of factors to affect PM-10 concentration in subway station
    • N. J. Kim, S. S. Lee, J. S. Jeon, J. H. Kim and M. Y. Kim, "Evaluation of factors to affect PM-10 concentration in subway station", Proceeding of KOSAE, pp. 571-573, 2006.
    • (2006) Proceeding of KOSAE , pp. 571-573
    • Kim, N.J.1    Lee, S.S.2    Jeon, J.S.3    Kim, J.H.4    Kim, M.Y.5
  • 2
    • 36049002543 scopus 로고    scopus 로고
    • Levels of particulate air pollution, its elemental compositions, determinants and health effects in metro systems
    • M. J. Nieuwenhuijsen, "Levels of particulate air pollution, its elemental compositions, determinants and health effects in metro systems", Atmospheric Environment, pp.7995-8006, 2007.
    • (2007) Atmospheric Environment , pp. 7995-8006
    • Nieuwenhuijsen, M.J.1
  • 3
    • 38049020120 scopus 로고    scopus 로고
    • Gray and neural network prediction of effluent from the wastewater treatment plant of industrial park using influent quality
    • T.Y. Pai. "Gray and neural network prediction of effluent from the wastewater treatment plant of industrial park using influent quality". Environmental Engineering Science., Vol.25, No.5, pp. 757-766, 2008.
    • (2008) Environmental Engineering Science , vol.25 , Issue.5 , pp. 757-766
    • Pai, T.Y.1
  • 6
    • 50849083804 scopus 로고    scopus 로고
    • Accounts of experience in the application of artificial neural networks in chemical engineering
    • D. M. Himmelblau, "Accounts of experience in the application of artificial neural networks in chemical engineering", Industrial & Engineering Chemistry, Vol.47, pp. 5782-5796, 2008.
    • (2008) Industrial & Engineering Chemistry , vol.47 , pp. 5782-5796
    • Himmelblau, D.M.1
  • 7
    • 69749098008 scopus 로고    scopus 로고
    • Estimation of a wastewater component using a hybrid artificial neural network in a wastewater treatment process
    • D. J. Choi and H. K. Park, "Estimation of a wastewater component using a hybrid artificial neural network in a wastewater treatment process", J. Korean Society of Water Quality, Vol.17, No.1, pp. 87-98, 2001.
    • (2001) J. Korean Society of Water Quality , vol.17 , Issue.1 , pp. 87-98
    • Choi, D.J.1    Park, H.K.2
  • 8
    • 0035422118 scopus 로고    scopus 로고
    • Data-based construction of feedback-corrected nonlinear prediction model using feedback neural networks
    • Y. D. Pan, S. W. Sung and J. H. Lee, "Data-based construction of feedback-corrected nonlinear prediction model using feedback neural networks", Control Engineering Practice, Vol.9, pp. 859-867, 2001.
    • (2001) Control Engineering Practice , vol.9 , pp. 859-867
    • Pan, Y.D.1    Sung, S.W.2    Lee, J.H.3
  • 10
    • 0036740519 scopus 로고    scopus 로고
    • Multi-class cancer classification via partial least squares with gene expression profiles
    • D. V. Nguyen and D.M. Rocke. "Multi-class cancer classification via partial least squares with gene expression profiles". Bioinformatics, Vol.18, No.9, pp. 1216-1226, 2002.
    • (2002) Bioinformatics , vol.18 , Issue.9 , pp. 1216-1226
    • Nguyen, D.V.1    Rocke, D.M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.