Genetic-based spatial clustering
Antonio Di Nola, Vincenzo Loia, Antonino Staiano · 2002
We propose a genetic-level clustering methodology able to cluster objects represented by R/sup p/ spaces. The unsupervised cluster algorithm is based on a fuzzy clustering c-means method that searches the best fuzzy partition of the universe assuming that the evaluation of each object respect to some features is unknown, but knowing that it belongs to circular region of R/sup 2/ space.