Stochastic configuration network (SCN), as a novel incremental generation model with
supervisory mechanism, has an excellent superiority in solving large-scale data regression …

Graph Convolutional Networks (GCNs), as a prominent example of graph neural networks,
are receiving extensive attention for their powerful capability in learning node …

Wind power generation is uncontrollable and non-adjustable green energy. The accurate
prediction of wind speed is of great significance to the operation and maintenance of wind …

Building upon pre-trained ViT models, many advanced methods have achieved significant
success in COVID-19 classification. Many scholars pursue better performance by increasing …

A learner model with fast learning and compact architecture is expected for industrial data
modeling. To achieve these goals during stochastic configuration networks (SCNs) …

To adapt to the reality of limited computing resources of various terminal devices in industrial
applications, a randomized neural network called stochastic configuration network (SCN) …

As we write this research paper, we notice an explosion in popularity of machine learning in
numerous fields (ranging from governance, education, and management to criminal justice …

The multimodal emotion recognition in conversation (ERC) task presents significant
challenges due to the complexity of relationships and the difficulty in achieving semantic …

This article concerns the co-design scheme of the adaptive event-triggered mechanism
(AETM) and asynchronous control for two-dimensional (2-D) Markov jump systems. First, we …

Complex fuzzy sets are an extension of type-1 fuzzy sets with complex-valued membership
functions. Over the last 20 years, time-series forecasting has emerged as the most important …