Stacking approaches for the design of a soft sensor for a sulfur recovery unit

IECON Proceedings (Industrial Electronics Conference)

Volumn , Issue , 2006, Pages 229-234

  Fortuna, L ^a   Graziani, S ^a   Napoli, G ^b   Xibilia, M G ^b  

^a UNIVERSITY OF CATANIA   (Italy)

^b UNIVERSITY OF MESSINA   (Italy)

Author keywords

Neural models; Plant monitoring; Refineries processes; Soft sensors; Stacking approaches

Indexed keywords

AGGLOMERATION; ARTIFICIAL INTELLIGENCE; COMPUTER SYSTEM RECOVERY; CURVE FITTING; DESULFURIZATION; ELECTRONICS INDUSTRY; ESTIMATION; FINANCIAL DATA PROCESSING; HYDROGEN; HYDROGEN SULFIDE; INDUSTRIAL ELECTRONICS; LEAST SQUARES APPROXIMATIONS; NONMETALS; PRINCIPAL COMPONENT ANALYSIS; REFINING; SENSORS; SULFUR; SULFUR DETERMINATION;

ACID GASES; ANNUAL CONFERENCE; ESTIMATION PERFORMANCE; MEASUREMENT DEVICES; MONITORING AND CONTROLLING; NEURAL MODELING; NEURAL MODELS; PARTIAL-LEAST-SQUARES; PLANT MONITORING; PRINCIPAL COMPONENT ANALYSIS (PCA); REFINERIES PROCESSES; SOFT SENSORS; STACKING APPROACHES; SULFUR RECOVERY UNIT;

NEURAL NETWORKS;

EID: 50249110771     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IECON.2006.347953     Document Type: Conference Paper

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