VMLP neural network design using optimization algorithms to predict spider suspend (Case Study: Watershed Dam Kardeh)

One of the most important processes of erosion and sediment transport in streams is the river most complex engineering issues.this process special effects on water quality indices, action suburbs floor and destroyed much damage to the river and also into the development plans Lack of continuity sediment sampling and measurement of many existing stations. due to the low number of hydrometric stations in Iran and the lack of continuity of sediment sampling and measuring in many existing stations, on one hand the exact amount of sediment load in many rivers in the country is not available and because of differences in climatic, hydrological and topographical conditions in the country, on the other hand, the preparation and calibration of sediment Erosion Models different regions, is unavoidableCalibration models of erosion and sedimentation in different locations is difficult and requires financial capital andthe time . the But evolutionary optimization algorithm able to resolve this problems of mathematical and experimental methods in this paper, a new optimization algorithm spiders can be made to education And the evolutionary pattern for input (discharge and precipitation) and rain-gauge gauging stations and Watershed Kardeh designated evolutionary algorithms and artificial network performance for 24 year 24-year dam catchment Kardeh for the period studied. In conclusion, the results proved that social spiders optimization algorithm t better resultspredic to for sediment in watershed Kardeh