%0 Journal Article %T Evaluating Adaptive Neuro-Fuzzy Inference System (ANFIS) To Assess Liquefaction Potential And Settlements Using CPT Test Data %J Journal of Soft Computing in Civil Engineering %I Pouyan Press %Z 2588-2872 %A Jangir, Himanshu Kumar %A Satavalekar, Rupali %D 2022 %\ 07/01/2022 %V 6 %N 3 %P 119-139 %! Evaluating Adaptive Neuro-Fuzzy Inference System (ANFIS) To Assess Liquefaction Potential And Settlements Using CPT Test Data %K settlements %K Adaptive Neuro-Fuzzy Inference System (ANFIS) %K Liquefaction %K Liquefaction-potential %K Sub-clustering %K MATLAB %R 10.22115/scce.2022.345237.1456 %X Liquefaction occurs when saturated, non-cohesive soil loses strength. This phenomenon occurs as the water pressure in the pores rises and the effective stress drops because of dynamic loading. Liquefaction potential is a ratio for the factor of safety used to figure out if the soil can be liquefied, and liquefaction-induced settlements happen when the ground loses its ability to support construction due to liquefaction. Traditionally, empirical and semi-empirical methods have been used to predict liquefaction potential and settlements that are based on historical data. In this study, MATLAB's Fuzzy Tool Adaptive Neuro-Fuzzy Inference System (ANFIS) (sub-clustering) was used to predict liquefaction potential and liquefaction-induced settlements. Using Cone Penetration Test (CPT) data, two ANFIS models were made: one to predict liquefaction potential (LP-ANFIS) and the other to predict liquefaction-induced settlements (LIS-ANFIS). The RMSE correlation for the LP-ANFIS model (input parameters: Depth, Cone penetration, Sleeve Resistance, and Effective stress; output parameters: Liquefaction Potential) and the LIS-ANFIS model (input parameters: Depth, Cone penetration, Sleeve Resistance, and Effective stress; output parameters: Settlements) was 0.0140764 and 0.00393882 respectively. The Coefficient of Determination (R2) for both the models was 0.9892 and 0.9997 respectively. Using the ANFIS 3D-Surface Diagrams were plotted to show the correlation between the CPT test parameters, the liquefaction potential, and the liquefaction-induced settlements. The ANFIS model results displayed that the considered soft computing techniques have good capabilities to determine liquefaction potential and liquefaction-induced settlements using CPT data. %U https://www.jsoftcivil.com/article_158237_8c5e7e119e44a5eda3e51ebda7574bd7.pdf