Utilization of self-organizing map and fuzzy clustering for site characterization using piezocone data

In this paper soft computing techniques, self-organizing maps and fuzzy clustering techniques have been proposed to isolate different layers in stratified soil based on available cone penetration test results. The results have been compared with that obtained from cone classification chart, hierarchical and K-mean clustering techniques. It was observed that variation in result with self-organizing map (SOM) and fuzzy clustering for isolating soil layers is marginal. These techniques are found to be efficient compared to hierarchical clustering technique. The results of K-mean clustering show that the identified soil strata are similar to that obtained from cone classification chart, SOM and fuzzy clustering.