Uncertainty measure is one of the most significant concepts and fundamental issues in
granular computing. Nowadays, there have been extensive studies on various uncertainty …

The purpose of this paper is twofold: firstly, to exhibit the existence of a reasonable
connection between fuzzy relations and (textural) fuzzy direlations in terms of fuzzy logical …

A framework is developed for gene expression analysis by introducing fuzzy Jaccard
similarity (FJS) and combining Łukasiewicz implication with it through weights in hybrid …

The work carried out during the Ph. D. in Medical Sciences and Biotechnology course tested
the application of machine learning models in several precision medicine topics. In …

Data analytics in granular computing framework is considered for several mining
applications, such as in video analysis, bioinformatics and online social networks which …

This paper divided Chinese manufacturing listed enterprises into six innovation persistence
patterns according to the innovation persistence and ownership structure, and identified …

This book contains the texture theory and its relations to rough sets and fuzzy sets. It
provides the intelligibility of the notions due to textures and presents concrete examples with …

Essentially, the motivation of various combinations of fuzzy sets and rough sets is to find
alternative formulations for imperfect data and knowledge. A fuzzy set is defined with the …

Self-organizing map (SOM) models perform clustering process based on a competitive
learning. The learning methods of these models involve neighborhood function such as …

Abstract Machine Learning (ML) is a method that aims to learn from data to identify patterns
and make predictions. Nowadays ML models have become ubiquitous, there are so many …