Parallel hybrid modeling methods for a full-scale cokes wastewater treatment plant

Journal of Biotechnology

Volumn 115, Issue 3, 2005, Pages 317-328

  Lee, Dae Sung ^a   Vanrolleghem, Peter A ^b   Jong, Moon Park ^a  

^a Pohang University of Science and Technology (POSTECH)   (South Korea)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

Hybrid modeling; Industrial wastewater treatment plant; Mechanistic model; Non parametric model; Partial least squares

Indexed keywords

COKE; DATA ACQUISITION; FEEDFORWARD NEURAL NETWORKS; INTEROPERABILITY; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; WATER TREATMENT PLANTS;

HYBRID MODELING; INDUSTRIAL WASTEWATER TREATMENT PLANT; MECHANISTIC MODEL; NON-PARAMETRIC MODEL; PARTIAL LEAST SQUARES;

WASTEWATER TREATMENT;

COKE;

ACCURACY; ACTIVATED SLUDGE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL STRUCTURE; HYBRID; LINEAR REGRESSION ANALYSIS; MOLECULAR DYNAMICS; MOLECULAR MECHANICS; MOLECULAR MODEL; POSITIVE FEEDBACK; PREDICTION; PRIORITY JOURNAL; SCIENCE; SPACE; WASTE WATER TREATMENT PLANT; BIOLOGICAL MODEL; BIOREACTOR; COMPARATIVE STUDY; COMPUTER SIMULATION; EVALUATION; FEEDBACK SYSTEM; INDUSTRIAL WASTE; METHODOLOGY; MICROBIOLOGY; PHYSIOLOGY; REGRESSION ANALYSIS; SEWAGE; STATISTICAL MODEL; WATER MANAGEMENT;

BIOREACTORS; COKE; COMPUTER SIMULATION; FEEDBACK; INDUSTRIAL MICROBIOLOGY; INDUSTRIAL WASTE; LEAST-SQUARES ANALYSIS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); SEWAGE; WATER MICROBIOLOGY; WATER PURIFICATION;

EID: 18944372441     PISSN: 01681656     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbiotec.2004.09.001     Document Type: Article

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