A Data Mining Approach for the Prediction of transport time scales in the Dez reservoir

Hydraulic time scales are of the key parameters in determining the water quality and sediment transport in an aquatic system. In recent years, soft computing tools as modern methods to generate intelligent systems have been used in different field of engineering and science. In this paper, by using multilayer artificial neural network and the results obtained from the simulation of the hydrodynamic processes in Dez reservoir, networks for prediction of mean residence times of river water and flushing time in the Dez reservoir in different days of simulation have been developed. Finally, the predicted results have been compared to the results obtained from the numerical modeling in other days of simulation and error has been cited. The compared data were in a good agreement with each other.

کلیدواژه ها:

Hydraulic time scales ، artificial neural networks ، residence time ، flushing time ، numerical modeling