Neural networks for prediction of wastewater treatment plant influent disturbances

IEEE AFRICON Conference

Volumn , Issue , 2007, Pages

  Kriger, C ^b   Tzoneva, R ^a  

^a IEEE

^b NONE

Author keywords

Data preparation; Forecasting; Neural networks; Wastewater treatment processes

Indexed keywords

ACTIVATED SLUDGE PROCESS; ARTIFICIAL INTELLIGENCE; BIOACTIVITY; CHEMICAL OXYGEN DEMAND; CHLORINE COMPOUNDS; FEEDFORWARD NEURAL NETWORKS; FORECASTING; IMAGE CLASSIFICATION; MULTILAYER NEURAL NETWORKS; NITROGEN; NONMETALS; OXYGEN; RECLAMATION; RECURRENT NEURAL NETWORKS; REINFORCEMENT LEARNING; SEWAGE PUMPING PLANTS; SEWAGE TREATMENT; VEGETATION; WASTEWATER RECLAMATION; WASTEWATER TREATMENT; WATER RECYCLING; WATER SUPPLY; WATER TREATMENT; WATER TREATMENT PLANTS;

ACTIVATED SLUDGE PROCESS (ASP); ACTIVATED SLUDGE PROCESSES; CONTROL STRATEGIES; DATA PREPARATION; FLOW-RATE; LOAD DISTURBANCES; MULTI-LAYER PERCEPTRON; NEURAL NETWORK MODELLING; ON-LINE SENSORS; PREDICTIVE PERFORMANCE; TOTAL KJELDAHL NITROGEN; WASTE WATER TREATMENT PLANT; WASTEWATER TREATMENT PROCESSES;

NEURAL NETWORKS;

EID: 48649103098     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AFRCON.2007.4401646     Document Type: Conference Paper

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