Immobilized cell biofilter: Results of performance and neural modeling strategies for NH3 vapor removal from waste gases

Aerosol and Air Quality Research

Volumn 9, Issue 3, 2009, Pages 379-384

  Rene, Eldon R ^a   Kim, Jung Hoon ^a   Park, Hung Suck ^a  

^a University of Ulsan   (South Korea)

Author keywords

Biofilter; Elimination capacity; Immobilization; Neural network; Prediction; Removal efficiency

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; COEFFICIENT VALUES; DATA MATRICES; DATA POINTS; DATA SETS; DATA-DRIVEN MODELING; ELIMINATION CAPACITY; FACTORIAL DESIGN; IMMOBILIZED CELLS; INLET CONCENTRATION; INPUT PARAMETER; INPUT/OUTPUT; INTERNAL NETWORK; KNOWLEDGE-BASED MODEL; LOADING RATE; MATRIX; MULTI-LAYER NETWORK; NETWORK TOPOLOGY; NEURAL MODELING; OUTPUT PARAMETERS; REMOVAL EFFICIENCIES; TEST MATRIX; TRAINING AND TESTING; VAPOR REMOVAL; WASTE GAS;

BIOFILTERS; BIOFILTRATION; CELL CULTURE; COMPUTER SIMULATION; ELECTRIC CONDUCTIVITY MEASUREMENT; ELECTRIC NETWORK TOPOLOGY; INLET FLOW; KNOWLEDGE BASED SYSTEMS; MATRIX ALGEBRA; REMOVAL; STATISTICAL TESTS; VAPORS;

NEURAL NETWORKS;

AMMONIUM; ARTIFICIAL NEURAL NETWORK; DATA SET; EXPERIMENTAL DESIGN; GENETIC ALGORITHM; IMMOBILIZATION; LOADING TEST; POLLUTANT REMOVAL; PRESSURE DROP; TOPOLOGY;

EID: 73449087953     PISSN: 16808584     EISSN: 20711409     Source Type: Journal    
DOI: 10.4209/aaqr.2008.10.0046     Document Type: Article

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