Clustering is an unsupervised learning technology, and it groups information (observations
or datasets) according to similarity measures. Developing clustering algorithms is a hot topic …

Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …

Compared to the intuitionistic fuzzy sets, the Pythagorean fuzzy sets (PFSs) can provide the
decision makers with more freedom to express their evaluation information. There exist …

This study mines customer satisfaction (CS) segments using almost 270 thousand
responses from a CS survey which ran in 140 e-commerce stores of a European country. To …

In the last decade, the application of membrane-inspired evolutionary algorithms in real-life
problems has attracted much attention due to their flexibility and parallelizability. Almost …

Machine learning (ML) has been an important arsenal in computational biology used to
elucidate protein function for decades. With the recent burgeoning of novel ML methods and …

Classical statistical learning techniques struggle to perform feature selection in high-
dimensional data that includes interaction effects ie, when independent feature/s influence …

While the number of people suffering from traumatic brain injury (TBI) has increased
considerably in recent years, the multiple deficits of these patients makes designing the …

Cluster analysis is one of the most useful tools for exploring the underlying structure of a
given data set and is being applied in a wide variety of engineering and scientific …

Artificial intelligence (AI) and machine learning (ML) have been active in various research
fields and improved results. However, most of them applied or focused on supervised …