In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …

Logistic regression (LR) continues to be one of the most widely used methods in data mining
in general and binary data classification in particular. This paper is focused on providing an …

Artificial Intelligence (AI) is becoming pervasive in most engineering domains, and railway
transport is no exception. However, due to the plethora of different new terms and meanings …

Large-scale data clustering is an essential key for big data problem. However, no current
existing approach is “optimal” for big data due to high complexity, which remains it a great …

Worldwide, there has been a rapid growth in interest in rough set theory and its applications
in recent years. Evidence of this can be found in the increasing number of high-quality …

Hyperspectral imaging fully portrays materials through numerous and contiguous spectral
bands. It is a very useful technique in various fields, including astronomy, medicine, food …

DBSCAN is a popular method for clustering multi-dimensional objects. Just as notable as
the method's vast success is the research community's quest for its efficient computation …

The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and
Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data …

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In recent years, many researchers have made a continuous effort to develop new and
efficient meta-heuristic algorithms to address complex problems. Hence, in this study, a …