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Evaluation for NDWCT Performance with Different Types of Packing Fills in Iraq Using ANN
Artificial Neural Network (ANN) is used to predicate experimental results for Natural Draft Wet Cooling Tower (NDWCT) rig using Levenberg-Marquardt back propagation algorithm in MATLAP. The experimental tests are done in hot and dry weather (Iraqi weather as an example). ANN results show good agreements with experimental results where average correlation coefficient (R) for all results is (0.994), average root mean square errors (RMSE) are (5.99, 0.91, 0.24, 0.51, 0.49, 0.2, and 5.46), anddoi:10.6084/m9.figshare.1385162.v1 fatcat:vmgbh6wxwfaxvih2fkqrckzw54