Modeling of the fluidized bed combustion process and NOx emissions using self-organizing maps: An application to the diagnosis of process states

Environmental Modelling and Software

Volumn 26, Issue 5, 2011, Pages 605-614

  Liukkonen, M ^a   Hiltunen, T ^b   Halikka E ^b   Hiltunen, Y ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

^b Foster Wheeler Power Group   (Finland)

Author keywords

Artificial neural network; Energy production; Fluidized bed; K means; Nitrogen oxide; Self organizing map

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COMBUSTION EFFICIENCIES; COMBUSTION PRO-CESS; EFFICIENT METHOD; EFFICIENT PROCESS; ENERGY PRODUCTIONS; HARMFUL EMISSIONS; INDUSTRIAL PROCESSS; INPUT DATAS; K-MEANS; K-MEANS CLUSTERING; PROCESS DATA; PROCESS FLUCTUATIONS; PROCESS STATE; TRAJECTORY ANALYSIS;

CONFORMAL MAPPING; FLUIDIZATION; FLUIDIZED BED PROCESS; FLUIDIZED BEDS; NITRIC OXIDE; NITROGEN; NITROGEN OXIDES; SELF ORGANIZING MAPS;

FLUIDIZED BED COMBUSTION;

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; CLUSTER ANALYSIS; COMBUSTION; DATA INTERPRETATION; EMISSION CONTROL; INDUSTRIAL PRACTICE; NITROGEN OXIDES; POWER GENERATION; POWER PLANT;

EID: 79251597159     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2010.12.002     Document Type: Article

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