Using artificial neural network for predicting heat transfer coefficient during flow boiling in an inclined channel

Abstract

heat transfer coefficient was selected to be its output. Via the method of trial-and-error, multiple layer perceptron network with 30 neurons in the hidden layer was attained as optimal arteficial neural network structure. The fact that is was enabled to predict accurately the heat transfer coefficient. For the training set, the mean relative absolute error is about 0.68 % and the correlation coefficient, is about 0.9997. As for the testing and validation set they are, respectively, about 0.60 % and 0.9998 and about 0.79 % and 0.9996.