عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Groundwater is one of the most important water sources in the arid and semi-arid areas. With regard to reducing the level of water tables due to overdraft in most of Iran's plains, the wells' flow rate has been greatly decreased and this issue necessitates the attention to planning the water resources. Determining the aquifers' thickness and type of alluvial and materials in aquifer is necessary for the development of the city planning and its infrastructures . with respect to the importance of estimating the depth of bed rock of aquifers for estimating the volume and planning the water resources in this study, the efficiency of artificial neural network models and neural fuzzy inference system were studied on the bed rock depth and its zoning in different parts of the aquifer.In this study, the parameters of geographical latitude and longitude, salinity, water table level, and the ground level were used as input, and tried to determine a suitable model for predicting the bed rock. Results showed that the neural network with R2 =0.835 RMSE =49. 488 meter with the inputs of geographical latitude and longitude and the groundwater level has a higher accuracy of ANFIS  models.
 -Root mean square error
 -Adaptive neuro fuzzy inference system