메뉴 건너뛰기




Volumn 19, Issue 10, 2004, Pages 919-928

Prediction of wastewater treatment plant performance using artificial neural networks

Author keywords

Biochemical oxygen demand; Model studies; Neural networks; Optimization; Prediction; Suspended solids; Waste water treatment

Indexed keywords

BIOCHEMICAL OXYGEN DEMAND; DATA REDUCTION; INFORMATION ANALYSIS; MATHEMATICAL MODELS; NEURAL NETWORKS;

EID: 3342965223     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2003.10.005     Document Type: Article
Times cited : (409)

References (21)
  • 2
    • 0035499548 scopus 로고    scopus 로고
    • Advanced hybrid fuzzy-neural controller for industrial wastewater treatment
    • Chen W.C., Chang N.B., Shieh W.K. Advanced hybrid fuzzy-neural controller for industrial wastewater treatment. Journal of Environmental Engineering. 127:(11):2001;1048-1059
    • (2001) Journal of Environmental Engineering , vol.127 , Issue.11 , pp. 1048-1059
    • Chen, W.C.1    Chang, N.B.2    Shieh, W.K.3
  • 4
    • 0032508908 scopus 로고    scopus 로고
    • Neural networks for prediction of ultrafiltration transmembrane pressure: Application to drinking water production
    • Delgrange V.N., Cabassud N., Cabassud M., Durand-Bourlier L., Laine J.M. Neural networks for prediction of ultrafiltration transmembrane pressure: application to drinking water production. Journal of Membrane Science. 150:1998;111-123
    • (1998) Journal of Membrane Science , vol.150 , pp. 111-123
    • Delgrange, V.N.1    Cabassud, N.2    Cabassud, M.3    Durand-Bourlier, L.4    Laine, J.M.5
  • 8
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology. II: Hydrologic applications, ASCE task committee on application of artificial neural networks in hydrology
    • Govindaraju R.S. Artificial neural networks in hydrology. II: hydrologic applications, ASCE task committee on application of artificial neural networks in hydrology. Journal of Hydrologic Engineering. 5:(2):2000;124-137
    • (2000) Journal of Hydrologic Engineering , vol.5 , Issue.2 , pp. 124-137
    • Govindaraju, R.S.1
  • 9
    • 0035988097 scopus 로고    scopus 로고
    • Advanced controlling of anaerobic digestion by means of hierarchical neural networks
    • Holubar P., Zani L., Hager M., Froschl W., Radak Z., Braun R. Advanced controlling of anaerobic digestion by means of hierarchical neural networks. Water Research. 36:2002;2582-2588
    • (2002) Water Research , vol.36 , pp. 2582-2588
    • Holubar, P.1    Zani, L.2    Hager, M.3    Froschl, W.4    Radak, Z.5    Braun, R.6
  • 10
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik K., Stinchcombe M., White H. Multilayer feedforward networks are universal approximators. Neural Networks. 2:1989;359-366
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 12
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for the prediction and forecasting of water resources variables: A review of modeling issues and applications
    • Maier H.R., Dandy G.C. Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications. Water Resources Research. 15:(1):2000;101-124
    • (2000) Water Resources Research , vol.15 , Issue.1 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 13
    • 0034808697 scopus 로고    scopus 로고
    • Intelligent waste-water treatment with neural-networks
    • Moreno-Alfonso N., Redondo C.F. Intelligent waste-water treatment with neural-networks. Water Policy. 3:2001;267-271
    • (2001) Water Policy , vol.3 , pp. 267-271
    • Moreno-Alfonso, N.1    Redondo, C.F.2
  • 14
    • 0034915469 scopus 로고    scopus 로고
    • Neural network modelling of Cryptosporidium and Giardia concentrations in the Delaware River, USA
    • Neelakantan T.R., Brion G.M., Lingireddy S. Neural network modelling of Cryptosporidium and Giardia concentrations in the Delaware River, USA. Water Science and Technology. 43:(12):2001;125-132
    • (2001) Water Science and Technology , vol.43 , Issue.12 , pp. 125-132
    • Neelakantan, T.R.1    Brion, G.M.2    Lingireddy, S.3
  • 15
    • 0036608090 scopus 로고    scopus 로고
    • Effectiveness of different artificial neural network training algorithms in predicting protozoa risks in surface waters
    • Neelakantan T.R., Lingireddy S., Brion G.M. Effectiveness of different artificial neural network training algorithms in predicting protozoa risks in surface waters. Journal of Environmental Engineering. 128:(6):2002;533-542
    • (2002) Journal of Environmental Engineering , vol.128 , Issue.6 , pp. 533-542
    • Neelakantan, T.R.1    Lingireddy, S.2    Brion, G.M.3
  • 18
    • 0347458328 scopus 로고    scopus 로고
    • periodic posting to the Usenet newsgroup comp.ai.neural-nets.
    • Sarle, W.S., 2002. "Neural Network FAQ, part 1 of 7: Introduction", periodic posting to the Usenet newsgroup comp.ai.neural-nets. Available at: ftp://ftp.sas.com/pub/neural/FAQ.html.
    • (2002) Neural Network FAQ, Part 1 of 7: Introduction
    • Sarle, W.S.1
  • 19
    • 0034746017 scopus 로고    scopus 로고
    • Chlorcast: A methodology for developing decision-making tools for chlorine disinfection control
    • Serodes J.B., Rodriguez M.J., Ponton A. Chlorcast: a methodology for developing decision-making tools for chlorine disinfection control. Environmental Modelling and Software. 16:2001;53-62
    • (2001) Environmental Modelling and Software , vol.16 , pp. 53-62
    • Serodes, J.B.1    Rodriguez, M.J.2    Ponton, A.3
  • 20
    • 0033377733 scopus 로고    scopus 로고
    • Neural fuzzy modeling of anaerobic biological wastewater treatment systems
    • Tay J.H., Zhang X. Neural fuzzy modeling of anaerobic biological wastewater treatment systems. Journal of Environmental Engineering. 125:(12):1999;1149-1159
    • (1999) Journal of Environmental Engineering , vol.125 , Issue.12 , pp. 1149-1159
    • Tay, J.H.1    Zhang, X.2
  • 21
    • 0033081947 scopus 로고    scopus 로고
    • Real-time water treatment process control with artificial neural networks
    • Zhang Q., Stanley S.J. Real-time water treatment process control with artificial neural networks. Journal of Environmental Engineering. 125:(2):1999;153-160
    • (1999) Journal of Environmental Engineering , vol.125 , Issue.2 , pp. 153-160
    • Zhang, Q.1    Stanley, S.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.