KNT-artificial neural network model for flux prediction of ultrafiltration membrane producing drinking water

Water Science and Technology

Volumn 50, Issue 8, 2004, Pages 103-110

  Oh, H K ^a   Yu, M J ^a   Gwon, E M ^b   Koo, J Y ^a   Kim, S G ^a   Koizumi, A ^c  

^a University of Seoul   (South Korea)

^b Myong Ji University   (South Korea)

^c TOKYO METROPOLITAN UNIVERSITY   (Japan)

Author keywords

KNT artificial neural network; Modeling; Permeate flux; Transmembrane pressure; Ultrafiltration

Indexed keywords

DATA REDUCTION; FLUXES; GROUNDWATER; ITERATIVE METHODS; KALMAN FILTERING; MATHEMATICAL MODELS; NEURAL NETWORKS; PILOT PLANTS; ULTRAFILTRATION;

FLUX PREDICTION; KALMAN NEURO TRAINING (KNT); SIGMOID ACTIVATION; TRANSMEMBRANE PRESSURE;

POTABLE WATER;

DRINKING WATER; GROUND WATER;

DRINKING WATER; FIBER MEMBRANE; FILTRATION; HOLLOW FIBER; NEURAL NETWORK; ULTRAFILTRATION; WATER TREATMENT;

ACCURACY; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; COMPUTER MODEL; CORRELATION COEFFICIENT; DATA ANALYSIS; EQUIPMENT DESIGN; EXPERIMENTAL DESIGN; HOLLOW FIBER MEMBRANE; INFORMATION PROCESSING; NONLINEAR SYSTEM; PREDICTION; STRUCTURE ANALYSIS; TURBIDITY; ULTRAFILTRATION; ULTRAVIOLET RADIATION; VALIDATION PROCESS; WASTE WATER TREATMENT PLANT; WATER QUALITY; WATER TEMPERATURE;

SIGMOIDEA;

EID: 8844287569     PISSN: 02731223     EISSN: None     Source Type: Journal    
DOI: 10.2166/wst.2004.0499     Document Type: Article

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