메뉴 건너뛰기




Volumn 40, Issue , 2013, Pages 140-150

Prediction analysis of a wastewater treatment system using a Bayesian network

Author keywords

Bayesian network; Inference; Modified sequencing batch reactor; Prediction analysis

Indexed keywords

BAYESIAN NETWORK MODELS; BIOLOGICAL REACTION; DECISION SUPPORTS; DYNAMIC PROCESS; EFFLUENT CONCENTRATIONS; EFFLUENT QUALITY; INFERENCE; INFLUENT LOADS; MODIFIED SEQUENCING BATCH REACTORS; NETWORK-BASED APPROACH; OPERATING CONDITION; OPERATIONAL CONDITIONS; PHYSICAL DATA; PHYSICAL FACTORS; WASTEWATER TREATMENT PLANTS; WASTEWATER TREATMENT SYSTEM;

EID: 84871727347     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2012.08.011     Document Type: Article
Times cited : (46)

References (39)
  • 1
    • 84855479905 scopus 로고    scopus 로고
    • Bayesian networks in environmental modelling
    • Aguilera P.A., et al. Bayesian networks in environmental modelling. Environmental Modelling and Software 2011, 26:1376-1388.
    • (2011) Environmental Modelling and Software , vol.26 , pp. 1376-1388
    • Aguilera, P.A.1
  • 2
    • 78049297856 scopus 로고    scopus 로고
    • An evaluation of automated structure learning with Bayesian networks: an application to estuarine chlorophyll dynamics
    • Alameddine I., et al. An evaluation of automated structure learning with Bayesian networks: an application to estuarine chlorophyll dynamics. Environmental Modelling and Software 2011, 26:163-172.
    • (2011) Environmental Modelling and Software , vol.26 , pp. 163-172
    • Alameddine, I.1
  • 3
    • 0026870035 scopus 로고
    • Bayesian networks for patient monitoring
    • Berzuini C., et al. Bayesian networks for patient monitoring. Artificial Intelligence in Medicine 1992, 4:243-260.
    • (1992) Artificial Intelligence in Medicine , vol.4 , pp. 243-260
    • Berzuini, C.1
  • 4
    • 31644438995 scopus 로고    scopus 로고
    • Assessing the decline of brown trout (Salmo trutta) in Swiss rivers using a Bayesian probability network
    • Borsuk M.E., et al. Assessing the decline of brown trout (Salmo trutta) in Swiss rivers using a Bayesian probability network. Ecological Modelling 2006, 192:224-244.
    • (2006) Ecological Modelling , vol.192 , pp. 224-244
    • Borsuk, M.E.1
  • 5
    • 1542548177 scopus 로고    scopus 로고
    • A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis
    • Borsuk M.E., et al. A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis. Ecological Modelling 2004, 173:219-239.
    • (2004) Ecological Modelling , vol.173 , pp. 219-239
    • Borsuk, M.E.1
  • 6
    • 4444329287 scopus 로고    scopus 로고
    • The use of Hugin to develop Bayesian networks as an aid to integrated water resource planning
    • Bromley J., et al. The use of Hugin to develop Bayesian networks as an aid to integrated water resource planning. Environmental Modelling and Software 2005, 20:231-242.
    • (2005) Environmental Modelling and Software , vol.20 , pp. 231-242
    • Bromley, J.1
  • 7
    • 33947728908 scopus 로고    scopus 로고
    • Bayesian networks and participatory modelling in water resource management
    • Castelletti A., Soncini-Sessa R. Bayesian networks and participatory modelling in water resource management. Environmental Modelling and Software 2007, 22:1075-1088.
    • (2007) Environmental Modelling and Software , vol.22 , pp. 1075-1088
    • Castelletti, A.1    Soncini-Sessa, R.2
  • 9
    • 0030212468 scopus 로고    scopus 로고
    • Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes
    • Chong H.G., Walley W.J. Rule-based versus probabilistic approaches to the diagnosis of faults in wastewater treatment processes. Artificial Intelligence in Engineering 1996, 10:265-273.
    • (1996) Artificial Intelligence in Engineering , vol.10 , pp. 265-273
    • Chong, H.G.1    Walley, W.J.2
  • 10
    • 0028969090 scopus 로고
    • Dynamic modelling of the activated sludge process: improving prediction using neural networks
    • Cote M., et al. Dynamic modelling of the activated sludge process: improving prediction using neural networks. Water Research 1995, 29:995-1004.
    • (1995) Water Research , vol.29 , pp. 995-1004
    • Cote, M.1
  • 11
    • 0001156075 scopus 로고    scopus 로고
    • Discretizing continuous attributes while learning Bayesian networks
    • Proceedings of the Thirteenth International Conference on Machine Learning
    • Friedman, N., Goldszmidt, M., 1996. Discretizing continuous attributes while learning Bayesian networks. In: Proceedings of the Thirteenth International Conference on Machine Learning, pp. 157-165.
    • (1996) , pp. 157-165
    • Friedman, N.1    Goldszmidt, M.2
  • 12
    • 2642578431 scopus 로고    scopus 로고
    • Activated sludge wastewater treatment plant modelling and simulation: state of the art
    • Gernaey K.V., et al. Activated sludge wastewater treatment plant modelling and simulation: state of the art. Environmental Modelling and Software 2004, 19:763-783.
    • (2004) Environmental Modelling and Software , vol.19 , pp. 763-783
    • Gernaey, K.V.1
  • 13
    • 0031642205 scopus 로고    scopus 로고
    • Bayesian network models for generation of crisis management training scenarios
    • AAAI, Madison, WI, USA, Anon (Ed.)
    • Grois E., et al. Bayesian network models for generation of crisis management training scenarios. Innovative Applications of Artificial Intelligence - Conference Proceedings 1998, 1113-1120. AAAI, Madison, WI, USA. Anon (Ed.).
    • (1998) Innovative Applications of Artificial Intelligence - Conference Proceedings , pp. 1113-1120
    • Grois, E.1
  • 14
    • 0032894554 scopus 로고    scopus 로고
    • Activated sludge model no. 3
    • AR1-AR1
    • Gujer W., et al. Activated sludge model no. 3. Water Science and Technology 1999, 39:183. AR1-AR1.
    • (1999) Water Science and Technology , vol.39 , pp. 183
    • Gujer, W.1
  • 16
    • 33947719959 scopus 로고    scopus 로고
    • Public participation modelling using Bayesian networks in management of groundwater contamination
    • Henriksen H.J., et al. Public participation modelling using Bayesian networks in management of groundwater contamination. Environmental Modelling and Software 2007, 22:1101-1113.
    • (2007) Environmental Modelling and Software , vol.22 , pp. 1101-1113
    • Henriksen, H.J.1
  • 17
    • 84871745284 scopus 로고    scopus 로고
    • Activated Sludge Models ASM1, ASM2, ASM2d and ASMS. Scientific and Technical Report.
    • Henze, M., 2007. Activated Sludge Models ASM1, ASM2, ASM2d and ASMS. Scientific and Technical Report.
    • (2007)
    • Henze, M.1
  • 18
    • 0032940453 scopus 로고    scopus 로고
    • Activated sludge model no. 2d, ASM2d
    • Henze M., et al. Activated sludge model no. 2d, ASM2d. Water Science and Technology 1999, 39:165-182.
    • (1999) Water Science and Technology , vol.39 , pp. 165-182
    • Henze, M.1
  • 21
    • 23344444108 scopus 로고    scopus 로고
    • Application of remote monitoring and automatic control system using neural network for small wastewater treatment plants in Korea
    • Lee H., et al. Application of remote monitoring and automatic control system using neural network for small wastewater treatment plants in Korea. Water Science and Technology 2005, 51:249-257.
    • (2005) Water Science and Technology , vol.51 , pp. 249-257
    • Lee, H.1
  • 22
    • 72649096233 scopus 로고    scopus 로고
    • Integrated water resources management of overexploited hydrogeological systems using object-oriented Bayesian networks
    • Molina J.L., et al. Integrated water resources management of overexploited hydrogeological systems using object-oriented Bayesian networks. Environmental Modelling and Software 2010, 25:383-397.
    • (2010) Environmental Modelling and Software , vol.25 , pp. 383-397
    • Molina, J.L.1
  • 24
    • 0035556585 scopus 로고    scopus 로고
    • Institute of Electrical and Electronics Engineers Inc., Dallas, TX, United states, 247-256
    • Myllymaki P., et al. B-course: a Web Service for Bayesian Data Analysis 2001, Institute of Electrical and Electronics Engineers Inc., Dallas, TX, United states, 247-256.
    • (2001) B-course: a Web Service for Bayesian Data Analysis
    • Myllymaki, P.1
  • 25
    • 46149134436 scopus 로고
    • Fusion, propagation, and structuring in belief networks
    • Pearl J. Fusion, propagation, and structuring in belief networks. Artificial Intelligence 1986, 29.
    • (1986) Artificial Intelligence , vol.29
    • Pearl, J.1
  • 26
    • 0042488498 scopus 로고
    • Handbook of Brain Theory and Neural Networks
    • Pearl J. Bayesian Networks 1995, Handbook of Brain Theory and Neural Networks, pp. 149-153.
    • (1995) Bayesian Networks , pp. 149-153
    • Pearl, J.1
  • 27
    • 84871798633 scopus 로고
    • (Ed.). Bayesian Networks.
    • Pearl, J. (Ed.) 1995b. Bayesian Networks.
    • (1995)
    • Pearl, J.1
  • 28
    • 33947726366 scopus 로고    scopus 로고
    • Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
    • Pollino C.A., et al. Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment. Environmental Modelling and Software 2007, 22:1140-1152.
    • (2007) Environmental Modelling and Software , vol.22 , pp. 1140-1152
    • Pollino, C.A.1
  • 29
    • 0030212929 scopus 로고    scopus 로고
    • The sensitivity of belief networks to imprecise probabilities: an experimental investigation
    • Pradhan M., et al. The sensitivity of belief networks to imprecise probabilities: an experimental investigation. Artificial Intelligence 1996, 85:363-397.
    • (1996) Artificial Intelligence , vol.85 , pp. 363-397
    • Pradhan, M.1
  • 30
    • 0035312268 scopus 로고    scopus 로고
    • Diagnosing upsets in anaerobic wastewater treatment using Bayesian belief networks
    • Sahely B.S.G.E., Bagley D.M. Diagnosing upsets in anaerobic wastewater treatment using Bayesian belief networks. Journal of Environmental Engineering 2001, 127:302-310.
    • (2001) Journal of Environmental Engineering , vol.127 , pp. 302-310
    • Sahely, B.S.G.E.1    Bagley, D.M.2
  • 31
    • 0026056182 scopus 로고
    • Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and interference algorithms
    • Shwe M.A., et al. Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and interference algorithms. Methods of Information in Medicine 1991, 30:241-255.
    • (1991) Methods of Information in Medicine , vol.30 , pp. 241-255
    • Shwe, M.A.1
  • 32
    • 0002979137 scopus 로고
    • An algorithm for fast recovery of sparse causal graphs
    • Spirtes P., Glymour C. An algorithm for fast recovery of sparse causal graphs. Social Science Computer Review 1991, 9:62-72.
    • (1991) Social Science Computer Review , vol.9 , pp. 62-72
    • Spirtes, P.1    Glymour, C.2
  • 33
    • 0042202691 scopus 로고    scopus 로고
    • Comparison of Estuarine water quality models for total maximum daily load development in Neuse River Estuary
    • Stow C.A., et al. Comparison of Estuarine water quality models for total maximum daily load development in Neuse River Estuary. Journal of Water Resources Planning and Management 2003, 129:307-314.
    • (2003) Journal of Water Resources Planning and Management , vol.129 , pp. 307-314
    • Stow, C.A.1
  • 34
    • 34047185270 scopus 로고    scopus 로고
    • Advantages and challenges of Bayesian networks in environmental modelling
    • Uusitalo L. Advantages and challenges of Bayesian networks in environmental modelling. Ecological Modelling 2007, 203:312-318.
    • (2007) Ecological Modelling , vol.203 , pp. 312-318
    • Uusitalo, L.1
  • 35
    • 0029509178 scopus 로고
    • Belief Networks for modelling and assessment of environmental change
    • Varis O. Belief Networks for modelling and assessment of environmental change. Environmetrics 1995, 6:439-444.
    • (1995) Environmetrics , vol.6 , pp. 439-444
    • Varis, O.1
  • 36
    • 33746428085 scopus 로고    scopus 로고
    • Policy analysis for the Tonle Sap Lake, Cambodia: a Bayesian network model approach
    • Varis O., Keskinen M. Policy analysis for the Tonle Sap Lake, Cambodia: a Bayesian network model approach. International Journal of Water Resources Development 2006, 22:417-431.
    • (2006) International Journal of Water Resources Development , vol.22 , pp. 417-431
    • Varis, O.1    Keskinen, M.2
  • 37
    • 0030832822 scopus 로고    scopus 로고
    • Bayesian approach to expert judgement elicitation with case studies on climatic change impact assessment on surface waters
    • Varis o., Kuikka S. Bayesian approach to expert judgement elicitation with case studies on climatic change impact assessment on surface waters. Climatic Change 1997, 37:539-563.
    • (1997) Climatic Change , vol.37 , pp. 539-563
    • Varis, O.1    Kuikka, S.2
  • 39
    • 79957838308 scopus 로고    scopus 로고
    • Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network
    • Young W.A., et al. Modeling net ecosystem metabolism with an artificial neural network and Bayesian belief network. Environmental Modelling and Software 2011, 26:1199-1210.
    • (2011) Environmental Modelling and Software , vol.26 , pp. 1199-1210
    • Young, W.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.