Prediction of Maximum Dry Density of Soil using Genetic Algorithm

Abstract

This paper deals with the application of genetic algorithm for the prediction of maximum dry density of soil. Compaction is the process by which soil is densified by reducing the air voids in it. The degree of compaction required for a given soil is measured in terms of its dry density which is maximum at the optimum moisture content. However this parameter, determined by laboratory compaction requires considerable time and effort. Hence its development from the index properties of soil helps to reduce the effort.. The development and generation of the genetic model was done using a large database containing about 200 case histories from various sources in the Ernakulam district, Kerala. The correlation of the predicted values with the actual values was determined and it was found that genetic algorithms can be used with a high degree of accuracy. The equations thus obtained can be used in the prediction of compaction parameters for new cases.