A neural network approach for prediction of critical submergence of an intake in still water and open channel flow for permeable and impermeable bottom

Computers and Fluids

Volumn 37, Issue 8, 2008, Pages 1040-1046

  Kocabaş, Fikret ^a   Ünal, Serap ^b   Ünal, Burhan ^a  

^a Faculty of Engineering and Architecture   (Turkey)

^b ERCIYES UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; CHANNEL FLOW; COMPUTER NETWORKS; FLUID MECHANICS; FOOD PROCESSING; HYDRAULICS; IMAGE CLASSIFICATION; LINEAR REGRESSION; METROPOLITAN AREA NETWORKS; NETWORK PROTOCOLS; NEURAL NETWORKS; OFFSHORE OIL WELL PRODUCTION; OPEN CHANNEL FLOW; PIPE; REGRESSION ANALYSIS; SHORE PROTECTION; TECHNOLOGY; WALL FLOW;

ARTIFICIAL NEURAL NETWORK (ANN) MODELS; ARTIFICIAL NEURAL NETWORK (ANNS); ELSEVIER (CO); EXPERIMENTAL RESULTS; EXPERIMENTAL STUDIES; HYDRAULIC ENGINEERING; INTAKE PIPES; MULTILINEAR REGRESSION (MLR); OPEN CHANNELS; STILL WATER;

AIR ENTRAINMENT;

EID: 45449116562     PISSN: 00457930     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compfluid.2007.11.002     Document Type: Article

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