| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 9690333 | Applied Thermal Engineering | 2005 | 12 Pages |
Abstract
Experimental data were obtained and used to train an artificial neural network in order to implement a mapping between easily measurable features such as environmental conditions, input and output water temperatures, solar radiation and flow rate of hot water.
Keywords
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Fluid Flow and Transfer Processes
Authors
Cuma Cetiner, Fethi Halici, Hamit Cacur, Imdat Taymaz,