![]() In contrast, MR_comp_LWD values have shown good agreement with MR_lab values among MR_back_LWD and MR_comp_LWD. MR_back_FWD and MR_back_LWD values of different soils by using Artificial Neural Network and Support Vector Machine techniques have shown the mean percentage variation (1.16–59.63%), correlation in terms of R² value (0.628–0.824), and RMSE value (0.51–20.49%) with MR_lab values. ![]() The comparative analysis was performed for MR_back by LWD (MR_back_LWD), MR_comp by LWD on subgrade (MR_comp_LWD), and MR_back by FWD (MR_back_FWD) with MR_lab values to assess the level of agreement. A series of in situ and laboratory investigations have been carried out on 190 test locations from 30 pavement sections of cohesive soils using Falling Weight Deflectometer (FWD), Light Weight Deflectometer (LWD), and Repeated Load Triaxial to determine backcalculated resilient moduli (MR_back), composite resilient moduli (MR_comp), and laboratory resilient modulus (MR_lab). ![]() This study aims to analyse the backcalculated cohesive subgrade moduli using various backcalculation approaches. ![]()
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