Permeability of soil is an important parameter in pavement performance. Permeability of stabilised soil is quite different than the parent soil. Fly Ash and Rice Husk Ash (RHA) are the waste products, which can be utilized as a potential stabilization material for altering the permeability of soil subgrade. Present study undertakes to establish the methodology to predict the permeability of fly ash and RHA stabilized CL soil (USCS classification) using Adaptive Neuro Fuzzy Approach. Voids ratio and degree of saturation noted during the permeability measurement in laboratory forms the basis for development of Adaptive Neuro Fuzzy Inference System (ANFIS) model. For the purpose of study 16 data sets of different combinations of fly ash and RHA are used for training the ANFIS model and testing was performed with 11 data sets of different combinations for the same soil. The study reported average training error of 0. 00010878 and testing error of 0. 001238. The developed architecture can be used to predict the permeability of stabilized soil subgrade (CL soil) with varying proportions of fly ash and RHA.

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Permeability Fly Ash Rice Husk Ash Soil Stabilisation Voids Ratio Degree Of Saturation Adaptive Neuro Fuzzy Inference System