Abstract
The development of mathematical models for cluster creation has been addressed by scientists in many fields. To our knowledge, functional cluster analysis (FCA) techniques have not been extended to cope with the problem of clustering particle-size distributions (PSDs) of sediments. The present study aims to introduce FCA as a tool for clustering different sediment samples according to their PSD. The procedure was applied to a case study on surface detrital sediment. Results were compared with a vector-based procedure: the k-means. The collected information suggests that FCA can be efficaciously employed to identify clusters in PSD of sediments. The proposed procedure may offer useful information for facies modeling in sedimentology.
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