Short-term wind power prediction is challenging due to the chaotic characteristics of wind
speed. Since, for wind power industries, designing an accurate and reliable wind power …

Electricity forecasting contributes to have an idea of the electricity needs for the expansion of
the electric system, the availability of the power plants according to the installed capacity …

Short-term traffic flow forecasting at isolated points is a fundamental yet challenging task in
many intelligent transportation systems. We present a novel long short-term memory (LSTM) …

In Internet of Vehicles (IoV), accurate traffic flow prediction is helpful for analyzing road
condition and then timely feedback traffic information to managers as well as travelers …

During an era of rapid growth in electricity demand throughout society, accurate forecasting
of electricity loads has become increasingly important to guarantee a stable power supply …

Deep neural network (DNN) with a complex structure and multiple nonlinear processing
units has achieved great success for feature learning in machinery fault diagnosis. Due to …

Wind speed forecasting plays a crucial role in reducing the risk of wind power uncertainty,
which is vital for power system planning, scheduling, control, and operation. However, it is …

With the development of automatic driving technology and the internet of vehicles,
platooning based on control of connected autonomous vehicles has become one of the most …

Recurrent neural networks (RNNs) are widely utilized in time series forecasting tasks. In
practical applications, there are noises in real-life time series data. A model's generalization …

With the development of transportation and the ever-improving of vehicular technology,
Artificial Intelligence (AI) has been popularized in Intelligent Transportation Systems (ITS) …