Our research is devoted to answering whether randomisation-based learning can be fully
competitive with the classical feedforward neural networks trained using backpropagation …

Solar energy has become crucial in producing electrical energy because it is inexhaustible
and sustainable. However, its uncertain generation causes problems in power system …

Electric energy demand forecasting is very important for electric utilities to procure and
supply electric energy for consumers sufficiently, safely, reliably, and continuously …

The recognition of hand signs is essential for several applications. Due to the variation of
possible signals and the complexity of sensor-based systems for hand gesture recognition, a …

Although Extreme Learning Machine (ELM) can learn thousands of times faster than
traditional slow gradient algorithms for training neural networks, ELM fitting accuracy is …

The role of electricity in our daily lives has been steadily growing, and the socioeconomic
data shows an indisputable link between the flourishing of modern societies and the …

Novel coronavirus 2019 has created a pandemic and was first reported in December 2019. It
has had very adverse consequences on people's daily life, healthcare, and the world's …

The extreme learning machine (ELM), a new learning algorithm for single hidden layer
feedforward neural networks (SLFN), has drawn interest of a large number of researchers …

Nowadays, the photovoltaic system which is one of the renewable energy sources has an
important role in generating electricity. To forecast photovoltaic system generation, the time …

Purpose Globally, cancer is the second largest cause of mortality. For the improvement of
cancer diagnosis, gene expression data plays a significant role. Cancer detection using …