Comparison of supervised learning techniques for atmospheric pollutant monitoring in a Kraft pulp mill

Journal of Computational and Applied Mathematics

Volumn 246, Issue , 2013, Pages 329-334

  Sainlez, Matthieu ^a   Heyen, Georges ^b  

^a CRISIA   (Belgium)

^b UNIVERSITY OF LIÈGE   (Belgium)

Author keywords

Dynamic approach; Pollutant monitoring; Supervised learning

Indexed keywords

BOILERS; COMPUTER SYSTEM RECOVERY; LEARNING ALGORITHMS; LEARNING SYSTEMS; LINEAR REGRESSION; NITROGEN OXIDES; PAPER AND PULP MILLS; POLLUTION; SUPERVISED LEARNING; POLLUTION DETECTION;

ATMOSPHERIC POLLUTANT MONITORING; DYNAMIC APPROACHES; KRAFT RECOVERY BOILERS; MULTI LAYER PERCEPTRON; MULTIPLE LINEAR REGRESSIONS; NEURAL NETWORK TECHNIQUES; POLLUTANT MONITORING; STATIONARY OPERATIONS;

KRAFT PULP;

DATA; KRAFT PULPS; NITROGEN OXIDES; PULP MILLS; IMPURITIES; KRAFT PULPING; MONITORING; PROBLEM SOLVING; REGRESSION ANALYSIS;

EID: 84923250685     PISSN: 03770427     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cam.2012.06.026     Document Type: Article

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