An autonomous approach to the mountain-clustering method

This paper presents an autonomous approach to the clustering algorithm based on a mountain function proposed by Yager and Filev (1994). It intends to answer the parameter selection problem and attenuate the effects of the granularity of the griding in algorithm's performance using a cluster reallocation procedure. The solving of those problems has greatly enhanced the possibility of achieving an autonomous mountain-clustering process. The proposed clustering approach is explained in detail and examples of its performance are analyzed.