Topological data analysis is a new theoretical trend using topological techniques to mine
data. This approach helps determine topological data structures. It focuses on investigating …

Abstract In the industrial 4.0 era, the development of an intelligent manufacturing business
model is driven by satisfying customer needs and intelligent algorithms. Enterprises are …

Clustering is a data analysis method that creates groups of objects according to a similarity
notion. Amongst the existing clustering algorithms, the possibilistic fuzzy c-means (PFCM) is …

Avian vocal individuality carries information that can be utilized as an alternative to physical
tagging of individuals. However, it is rarely used in conservation tasks despite rapidly …

This paper deals with the problem of determining the most appropriate number of clusters in
a fuzzy Mahalanobis partition. First, a new fuzzy Mahalanobis incremental algorithm is …

Crying is how babies express their needs eliciting care and providing information to parents
and physicians about their health and physical status. Automatic crying-pattern analysis is …

Abstract The Consillium Academica initiative, spearheaded by the academic vice deanship
of the Faculty of Sciences at Universidad Nacional de Colombia in Bogotá, is based on a …

The article discusses fuzzy clustering of complexvalued data and methods for evaluating the
quality of fuzzy clustering to determine the optimal number of clusters: Xie-Beni index, fuzzy …

This paper presents a fuzzy proportional membership model for clustering (FCPM). Unlike
the other clustering models, FCPM requires that each entity may express an extent of each …

Abstract The Consillium Academica initiative, spearheaded by the academic vicedeanship
of the Faculty of Sciences at Universidad Nacional de Colombia in Bogotá, is based on a …