Ability evaluation of hybrid SOM-FL model for hydraulic conductivity estimating in Tabriz city subway area

Increasing development of engineering projects construction such as city subway needs appropriate investigation, management and control of groundwater. Therefore, precise estimation of hydrogeological parameters such as hydraulic conductivity is the most important factor in studies and modeling of groundwater and geotechnical issues. In recent decades, various laboratory and field methods exist for estimating this parameter, but estimation of hydraulic conductivity using these methods due to the heterogeneity and anisotropy hydrogeological environments is costly, time-consuming and inherent uncertain. In this study, three fuzzy inference methods, Sugeno (SFIS), Mamdani fuzzy inference model (MFIS) and Larsen Fuzzy Inference System (LFIS) that is suitable for handling the uncertain data, was adopted to estimate the hydraulic conductivity in Tabriz city subway area. After, the hybrid SOM-FL model was presented to improve efficiency of individual model and solve heterogeneity problem of the Tabriz city aquifer. Based the evaluation criterions R2 and RMSE the results of individual models are acceptable but the proposed hybrid model improved, R2 in train and test stage, 18% and 15.4 percent, respectively.