Artificial neural network-based modeling of pressure drop coefficient for cyclone separators

Chemical Engineering Research and Design

Volumn 88, Issue 5-6, 2010, Pages 606-613

  Zhao, Bingtao ^a   Su, Yaxin ^b  

^a UNIVERSITY OF SHANGHAI FOR SCIENCE AND TECHNOLOGY   (China)

^b DONGHUA UNIVERSITY   (China)

Author keywords

Artificial neural network; Cross validation; Cyclone separators; Modeling; Optimized search; Pressure drop coefficient

Indexed keywords

APPROXIMATE RESULTS; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; BACK-PROPAGATION NEURAL NETWORKS; COMPLEX RELATIONSHIPS; CPU TIME; CROSS VALIDATION; GENERALIZATION PERFORMANCE; GENERALIZED REGRESSION NEURAL NETWORKS; GEOMETRICAL DIMENSIONS; MEAN SQUARED ERROR; OPTIMAL PARAMETER; PRESSURE DROP COEFFICIENTS; RADIAL BASIC FUNCTION; SEARCH TECHNIQUE; TRAINING SAMPLE;

CYCLONE SEPARATORS; OPTIMIZATION; PRESSURE DROP; STORMS;

NEURAL NETWORKS;

EID: 77953610108     PISSN: 02638762     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cherd.2009.11.010     Document Type: Article

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