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Simulation of Groundwater by using Support Vector Model and Comparing That with the Neuro-Fuzzy Model (ANFIS) :


Mehrdad Fereydooni, Hojat Tajbakhsh


Vol. 17  No. 6  pp. 76-80


Undoubtedly, the best way for recognition of qualitative treatments of groundwater resources is conducting long time researches, gathering the basic data for long periods and obtaining results from these data. In this research, the efficiency of support vector model (SVM) and the neuro- fuzzy inference system (ANFIS( was investigated for simulation of groundwater level based on the available data in a 19 statistical period including precipitation and the average of groundwater level ( since 1994 since 2013). In the present research, the different scenarios were reviewed for intelligent inputs models and the performance of above mentioned models was investigated based on the statistical indexed such as correlation coefficient (R) and mean square error (MSE). Finally, the suggested results of proper performance of both support vector models of (MSE=0.0001and R=0.9867) and ANFIS (MSE=0.0003, R=0.9820) in simulating the plain groundwater level are considered.


groundwater level, support vector model (SVM), Neuro-Fuzzy Inference System (ANFIS)