Kernel-based learning (KBL) methods have recently become prevalent in many engineering
applications, notably in signal processing and communications. The increased interest is …

For many years, artificial neural networks (ANNs) have been studied and used to model
information processing systems based on or inspired by biological neural structures. They …

Timely and accurate prediction of key indicators of sewage is the focus of intelligent sewage
treatment research. But traditional deep learning model performs unsteadily in the case of …

Processing big data streams through machine learning algorithms has various challenges,
such as little time to train the models, hardware memory constraints, and concept drift. In this …

Accurately forecasting housing prices will enable investors to attain profits, and it can
provide information to stakeholders that housing prices in the community are falling …

With the differences of customization attributes, the changes of the implementing stages of
rules and different selling countries, the contents of the check value of RoHS (Restriction of …

The kernel method has become a useful trick and has been widely applied to various
learning models to extend their nonlinear approximation and classification capabilities. Such …

In this paper we introduce online semi-supervised growing neural gas (OSSGNG), a novel
online semi-supervised classification approach based on growing neural gas (GNG) …

The self-organizing map (SOM) is one of the popular clustering and data visualization
algorithms and has evolved as a useful tool in pattern recognition, data mining since it was …

K-means is one of the most commonly used clustering algorithms, with diverse scope for
implementation in the signal processing, artificial intelligence and image processing fields …