Kurnaz, Talas FikretKaya, Yilmaz2024-12-242024-12-2420201866-75111866-7538https://doi.org/10.1007/s12517-020-5171-9https://hdl.handle.net/20.500.12604/6213The compaction parameters of soils known as the optimum moisture content (OMC) and maximum dry density (MDD) are necessary for the geotechnical engineering applications such as the fills, embankments, and dams. However, it takes a long time to determine the compaction parameters due to the laboratory test procedure. It was aimed to estimate the compaction parameters of soils with four soft computing methods and also to compare the performance of the methods in this study. For this purpose, a wide database consisting the index and standard proctor (SP) test results were used. Although all AI methods used in this study are successful on estimation of the MDD and OMC parameters, it was seen that the ELM method was the most successful method on the prediction of compaction parameters.eninfo:eu-repo/semantics/closedAccessCompactionMaximum dry densityOptimum moisture contentSoft computingArticle134Q3WOS:000513629600002N/A2-s2.0-8507913150210.1007/s12517-020-5171-9