Existing clustering approaches are usually restricted to crisp clustering, where objects just
belong to one cluster; meanwhile there are some applications where objects could belong to …

Data streams have arisen as a relevant research topic during the past decade. They are real‐
time, incremental in nature, temporally ordered, massive, contain outliers, and the objects in …

Abstract A Generalized Entropy based Possibilistic Fuzzy C-Means algorithm (GEPFCM) is
proposed in this paper for clustering noisy data. The main objective of GEPFCM is to …

The need of fuzzy clustering arises in many real-world applications such as clum** the
users based on their web browsing behavior where the behavior of a user can be similar to …

Abstract Machine Learning (ML) has become an essential tool for modeling complex
phenomena, offering robust predictions and comprehensive data analysis. Nevertheless, the …

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the
security of information systems. IDS can be used to detect the abuse by intruders who try to …

Mining web usage data of e-business organizations is essential to provide knowledge about
clients' web utilization patterns, which can help these businesses in landing at vital business …

Many supervised clustering algorithms have been developed to find the optimal clusters for
static datasets by presetting some parameters, but they are seldom suitable for dynamic …

Abstract The use of Machine Learning (ML) and optimization for control applications in
enhancing performance, replicating expert behaviors, and addressing other complex …

Abstract In Robust Control and Data Driven Robust Control design methodologies, multiple
plant transfer functions or a family of transfer functions are considered and a common …