Performance prediction of wet cooling tower using artificial neural network under cross-wind conditions

International Journal of Thermal Sciences

Volumn 48, Issue 3, 2009, Pages 583-589

  Gao, Ming ^a   Sun, Feng zhong ^a   Zhou, Shou jun ^b   Shi, Yue tao ^a   Zhao, Yuan bin ^a   Wang, Nai hua ^a  

^a SHANDONG UNIVERSITY   (China)

^b SHANDONG JIANZHU UNIVERSITY   (China)

Author keywords

BP network; Cooling tower; Cross wind; Heat and mass transfer

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION ALGORITHMS; BUILDINGS; COOLING; COOLING TOWERS; CORRELATION METHODS; HEAT TRANSFER; MASS TRANSFER; MEAN SQUARE ERROR; MIXED CONVECTION; NEURAL NETWORKS; TOWERS; VEGETATION;

ANN MODELS; ANN TRAININGS; ARTIFICIAL NEURAL NETWORKS; BACK PROPAGATIONS; BP ALGORITHMS; BP NETWORK; CIRCULATING WATERS; CORRELATION COEFFICIENTS; CROSS-WIND; GRADIENT DESCENT METHODS; HEAT AND MASS TRANSFER; HIDDEN LAYERS; INLET WATER TEMPERATURES; INPUT LAYERS; LAB EXPERIMENTS; MEAN SQUARES; NETWORK MODELS; NODE NUMBERS; OUTPUT LAYERS; OUTPUT PARAMETERS; PERFORMANCE PREDICTIONS; STATISTICAL PERFORMANCES; THERMAL PERFORMANCES; WET COOLING; WIND CONDITIONS; WIND VELOCITIES;

BACKPROPAGATION;

EID: 58149139421     PISSN: 12900729     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijthermalsci.2008.03.012     Document Type: Article

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