Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

Carbon emissions play a crucial role in inducing global warming and climate change.
Accurate and stable carbon emissions forecasting is beneficial for formulating emissions …

Accurately and automatically recognizing the emotional states of human beings is the
central task in affective computing. The electroencephalography (EEG) data, generated from …

In an electroencephalogram-(EEG-) based brain–computer interface (BCI), a subject can
directly communicate with an electronic device using his EEG signals in a safe and …

Electroencephalogram (EEG) signals are generated from central nervous system which are
difficult to disguise, leading to its popularity in emotion recognition. Recently, semi …

The accurate prediction of daily carbon dioxide (CO 2) emissions is crucial for grasping the
real-time dynamics of CO 2 emissions and formulating emission reduction policies. The use …

In this paper, we first integrate normalization to the Ensemble Deep Random Vector
Functional Link network (edRVFL). This re-normalization step can help the network avoid …

Spectral clustering is a group of graph-based clustering methods in which the columns of the
scaled cluster indicator matrix can be obtained by stacking the eigenvectors of the Laplacian …

In electroencephalography (EEG)-based affective brain–computer interfaces (aBCIs), there
is a consensus that EEG features extracted from different frequency bands and channels …

Randomized neural networks have become more and more attractive recently since they
use closed-form solutions for parameter training instead of gradient-based approaches …