Abstract
AbstractThis paper presents the application of artificial neural network (ANN) in saturator. Phase Doppler Anemometry (PDA) is utilized to investigate the distribution of water droplets diameter and velocity in the saturator. The data obtained from experiment is used as input-output of ANN. Before using ANN method, some prerequisites have to be processed, including the selection of the number of input and output variables, hidden layer neurons, the network architecture and the normalization of data etc. The results indicate that the trained ANN can provide accurate prediction values which agree with real experimental data closely.KeywordsArtificial Neural NetworkHide LayerArtificial Neural Network ModelWater DropletHide Layer NeuronThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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