Hierarchical neural network modeling approach to predict sludge volume index of wastewater treatment process

IEEE Transactions on Control Systems Technology

Volumn 21, Issue 6, 2013, Pages 2423-2431

  Han, Honggui ^a   Qiao, Junfei ^a  

^a BEIJING UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Extended extreme learning machine (EELM); hierarchical; predicting; radial basis function neural network; sludge volume index (SVI); wastewater treatment process (WWTP)

Indexed keywords

EXTREME LEARNING MACHINE; HIERARCHICAL; PREDICTING; RADIAL BASIS FUNCTION NEURAL NETWORKS; SLUDGE VOLUME INDEX; WASTEWATER TREATMENT PROCESS;

ACTIVATED SLUDGE PROCESS; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; NETWORK LAYERS; QUALITY CONTROL; RADIAL BASIS FUNCTION NETWORKS; RECLAMATION; SEWAGE SLUDGE; WASTEWATER TREATMENT;

FORECASTING;

EID: 84886589689     PISSN: 10636536     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCST.2012.2228861     Document Type: Article

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