Clustering is a powerful machine learning method for discovering similar patterns according
to the proximity of elements in feature space. It is widely used in computer science …

Resource management in data centres continues to be a critical problem due to increased
infrastructure complexity and dynamic workload conditions. Workload and energy …

A cooperative game theory framework is proposed to solve multi-robot task allocation
(MRTA) problems. In particular, a cooperative game is built to assess the performance of …

Fuzzy-means method (FCM) is a popular clustering method, which uses alternating iteration
algorithm to update membership matrix and center matrix of size. However, original FCM …

Abstract Background and Objective Medical hyperspectral images (MHSIs) are used for a
contact-free examination of patients without harmful radiation. However, high-dimensionality …

In real-world scenarios, identifying the optimal number of clusters in a dataset is a difficult
task due to insufficient knowledge. Therefore, the indispensability of sophisticated automatic …

Overlap** community detection plays an important role in studying social networks. The
existing overlap** community detection methods seldom perform well on networks with …

Classification is a vital task in machine learning. By learning patterns of samples of known
categories, the model can develop the ability to distinguish the categories of samples of …

Unsupervised anomaly detection in time series remains challenging, due to the rare and
complex patterns of anomalous data. Previous change point detection methods based on …

Data stream clustering plays an important role in data stream mining for knowledge
extraction. Numerous researchers have recently studied density-based clustering algorithms …