Global carbon emissions caused by fossil fuels and diesel-based vehicles have urged the
necessity to move toward the development of electric vehicles and related battery storage …

Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

Tradition K-means clustering algorithm is easy to fall into local optimum, poor clustering
effect on large capacity data and uneven distribution of clustering centroids. To solve these …

The improvement of enterprise competitiveness depends on the ability to match segmented
customers in a competitive market. In this study, we propose a customer segmentation …

In this research, we propose an enhanced Grey Wolf Optimizer (GWO) for designing the
evolving Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) networks for …

Abstract Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO) algorithm are
two popular swarm intelligence optimization algorithms and these two algorithms have their …

Medical technological advancements have led to the creation of various large datasets with
numerous attributes. The presence of redundant and irrelevant features in datasets …

K-means clustering algorithm is a partitional clustering algorithm that has been used widely
in many applications for traditional clustering due to its simplicity and low computational …

Since the multidepot vehicle routing problem with time windows and three-dimensional
loading constraints (MDVRPTW-TDLC) is a multiconstraint and combinatorial optimization …

Automatic segmentation of salient objects in real-world images has gained increasing
interests owing to its popularity in diverse real-world applications, such as autonomous …