Purpose Developing automated methods to identify task‐driven quality assurance (QA)
procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use …

The efforts of the European Union (EU) in the energy supply domain aim to introduce
intelligent grid management across the whole of the EU. The target intelligent grid is …

The aim of this paper is to present a review of methods for incremental Support Vector
Machines (SVM) learning and their adaptation for data stream classification in evolving …

Ensemble learning is one of the machine learning approaches, which can be described as
the process of combining diverse models to solve a particular computational intelligence …

In the anti-jamming field of radio communication, the problem of online and multiclass
jamming recognition is fundamental to implement reasonable anti-jamming measures. The …

The complexity of certain problems causes that classical methods for finding exact solutions
have some limitations. In this paper we propose an incremental heterogeneous ensemble …

Support Vector Data Description (SVDD) has a limitation for dealing with a large dataset or
online learning tasks. This work investigates the practice of credit scoring and proposes a …

The application of Support Vector Machine (SVM) over data stream is growing with the
increasing real-time processing requirements in classification field, like anomaly detection …

Support Vector machine is one of the most popular and efficient algorithms in machine
learning. There are several versions of this algorithm, the latest of which is the fuzzy least …