Abstract

It is important to protect the soil and groundwater from the pollution originating from leachate. Compacted clay soils is a favorable and economic method to protect groundwater and soil against contamination. In this study, compaction tests of leachate was done by using Modified Proctor method. The effects of microbial activity on the permeability of compacted clay soils were analyzed and the obtained data were applied to k-Nearest Neighbors (k-NN) method to predict the permeability of soils in landfill sites. k-NN method, which is a non-parametric distance-based machine learning method and widely used in classification and regression problems was applied to model the relationship between the microorganisms and the permeability. By using k-NN classification method, total heterotrophic bacteria and fungi microorganisms correctly classified the permeability variance as 78.59% and 77.31% success rate, respectively. Also, k-NN modelling was set on regression mode to predict permeability value and produced similar success rates in regression similarity with the actual value. Although, fecal coliforms and fecal streptococci microorganisms had neutral or negative contribution on analyses. For prediction accuracy and regression analysis, the k-NN method was considered for modeling the data. The results of the k-Nearest Neighbors method proved that it is a promising tool for predicting permeability of compacted clay by using microbial activity.

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