Modeling of manufacturing processes by learning systems: The naïve Bayesian classifier versus artificial neural networks

Journal of Materials Processing Technology

Volumn 164-165, Issue , 2005, Pages 1430-1435

  Perzyk, Marcin ^a   Biernacki, Robert ^a   Kochański, Andrzej ^a  

^a WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Artificial neural networks; Learning systems; Manufacturing process; Modeling; Na ve Bayesian classifier

Indexed keywords

COMPUTER SIMULATION; ERROR DETECTION; MANUFACTURE; MATHEMATICAL MODELS; NEURAL NETWORKS; PARAMETER ESTIMATION; REGRESSION ANALYSIS; TOPOLOGY; INDUSTRIAL ENGINEERING; MODELS; PRODUCTION ENGINEERING;

MANUFACTURING PROCESS; MATHEMATICAL TOOLS; MODELING; NÄIVE BAYESIAN CLASSIFIER;

LEARNING SYSTEMS;

BAYESIAN CLASSIFIER; IMPORTANCE FACTORS; INDUSTRIAL DATUM; MANUFACTURING PROCESS; MODELING CAPABILITIES; PREDICTION ERRORS;

EID: 17844369454     PISSN: 09240136     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmatprotec.2005.02.043     Document Type: Article

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