Energy plays an essential role in economic growth. It is expected that the electricity
consumption projections in Egypt will exceed electricity generation capabilities for the …

Recurrent Neural Networks (RNN) are basically used for applications with time series and
sequential data and are currently being used in embedded devices. However, one of their …

This study aims to predict the number of accidents in the National Iranian Oil Products
Distribution Company (NIOPDC) as a case study in 2022 according to the database …

Biosignal monitoring using wearable and implantable devices (WIMDs) is driving the advent
of highly personalized medicine. However, such devices may suffer from the same faulty …

A seca meteorológica é um evento atmosférico temporário e recorrente, originado pela falta
de precipitação por um período considerável em uma determinada área. A parte noroeste …

A nonlinear autoregressive neural network (NARNN) model is a feedforward neural network
for handling complex nonlinear time series problem. In this study, the tangent sigmoid …

Motivated by the unpredictability of stochastic time series, this paper presents an alternative
deep learning approach to characterize long-term stochastic fluctuation patterns. The …

Production activities suffered setbacks due to incessant machine breakdown caused by an
incipient fault that occurred without prior notification has become worrisome to industrialists …

Abstract The Internet of Medical Things (IoMT) is a rapidly advancing field that relies heavily
on semi-or closed-loop Wearable and Implantable Medical Devices (WIMDs). In recent …

A nonlinear autoregressive neural network (NARNN) model is a feedforward neural network
for handling complex nonlinear time series problems. In this study, the tangent sigmoid …