With randomly generated weights between input and hidden layers, a random vector
functional link network is a universal approximator for continuous functions on compact sets …

Intelligent lighting systems and surveillance systems have become an important part of
intelligent buildings. However, the current intelligent lighting system generally adopts …

Abstract Machine learning techniques are being increasingly used for detection and
diagnosis of diseases for its accuracy and efficiency in pattern classification. In this paper …

To address time consuming and parameter sensitivity in the emerging decomposition-
ensemble models, this paper develops a non-iterative learning paradigm without iterative …

Grain size is one of the most important parameters for metallographic microstructure
analysis, which can partly determine the material performance. The measurement of grain …

Inspired by the interesting idea of randomization, some powerful but time-consuming
decomposition-ensemble learning paradigms can be extended into extremely efficient and …

Ensemble classifiers with random vector functional link network have shown improved
performance in classification problems. In this paper, we propose two approaches to solve …

The use of surveillance video cameras in public transport is increasingly regarded as a
solution to control vandalism and emergency situations. The widespread use of cameras …

Cryptocurrencies have carved out a significant presence in financial transactions during the
past few years. Cryptocurrency market performs similarly to other financial markets with …

Electroencephalography (EEG) signals are used to evaluate the activities of the brain. For
the accidents occurring on the road, one of the primary reasons is driver fatigueness and it …