Performance Evaluation of Artificial Neural Networks Softwares in Prediction of Hydraulic Data

نویسندگان

  • ABDEL-AZIM M. NEGM
  • MOHAMED A. SHOUMAN
چکیده

Several artificial neural work (ANNs) software packages are available and being under use by researchers in different fields of sciences and engineering. These types of software could be used successfully by hydraulic engineers to simulate and predict hydraulic information. In this paper, three ANNs packages are used separately to predict hydraulic data of scour and hydraulic jump phenomena. These packages are NN toolbox of Matlab, Neural Connections and Neuro-Solutions. The performance of the packages are evaluated by comparative prediction of each software and by the measured hydraulic data. The correlation coefficient (R) and the mean relative absolute error (MRE) are used in the evaluation performance of each package. Recommendations and conclusions are presented.

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تاریخ انتشار 2004