Application of artificial neural networks to estimate wastewater treatment plant inlet biochemical oxygen demand

Environmental Progress

Volumn 27, Issue 4, 2008, Pages 439-446

  Dogan, Emrah ^a   Ates, Asude ^a   Yilmaz, Ece Ceren ^a   Eren, Beytullah ^a  

^a SAKARYA UNIVERSITY   (Turkey)

Author keywords

Artificial neural network; Multiple linear regression model; Wastewater treatment plant; Water quality

Indexed keywords

BACKPROPAGATION; BIOCHEMICAL OXYGEN DEMAND; BLOCK CODES; ERROR STATISTICS; ERRORS; HYDRAULIC MODELS; LINEAR REGRESSION; MEAN SQUARE ERROR; NETWORK MANAGEMENT; NEURAL NETWORKS; NONMETALS; OXYGEN; PHOSPHORUS; PLANNING; QUALITY MANAGEMENT; REGRESSION ANALYSIS; SEWAGE PUMPING PLANTS; VEGETATION; WASTEWATER; WASTEWATER RECLAMATION; WASTEWATER TREATMENT; WATER CONSERVATION; WATER MANAGEMENT; WATER POLLUTION; WATER QUALITY; WATER RECYCLING; WATER RESOURCES; WATER SUPPLY; WATER TREATMENT; WATER TREATMENT PLANTS;

A COEFFICIENTS; ANN MODELS; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; BIOCHEMICAL TREATMENTS; COEFFICIENT OF DETERMINATIONS; DATA SETS; MEAN SQUARES; MODEL PERFORMANCES; MULTIPLE LINEAR REGRESSION MODEL; MULTIPLE LINEAR REGRESSION MODELS; RELATIVE ERRORS; SUSPENDED SOLIDS; TIME PERIODS; TOTAL NITROGENS; TOTAL PHOSPHORUSES; WASTE WATER TREATMENT PLANTS; WASTEWATER TREATMENT PLANT; WATER DISCHARGES; WATER QUALITY DATUMS; WATER QUALITY MANAGEMENTS;

CHEMICAL OXYGEN DEMAND;

EID: 56849087528     PISSN: 02784491     EISSN: 10982280     Source Type: Journal    
DOI: 10.1002/ep.10295     Document Type: Article

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