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

Inspired by the ensemble strategy of machine learning, deep random vector functional link
(dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different …

This work investigated the use of an ensemble deep random vector functional link (edRVFL)
network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low …

As an epigenetic modification that plays an important role in modifying gene function and
controlling gene expression during cell development, DNA N4-methylcytosine (4mC) is still …

Efficient forecasting of ship order books holds immense significance in the maritime industry,
enabling companies to optimize their operations, allocate resources effectively, and make …

The incremental version of randomized neural networks provides a greedy constructive
algorithm for the shallow network, which adds new nodes through different stochastic …

Knowledge distillation (KD) is a conventional method in the field of deep learning that
enables the transfer of dark knowledge from a teacher model to a student model …

Network selection in heterogeneous wireless networks (HWNs) is a complex issue that
requires a thorough understanding of service features and user preferences. This is …

Traditionally, testing is done first at end of the design phase; however, this is no longer the
case. Testing, finding, and categorising bugs, as well as releasing the development changes …

Fault diagnosis of rotating machines is essential for the safe and efficient operation of
maritime vessels. It prevents potential failures in rotating machines in maritime systems …