Predicting traffic flow is vital for optimizing transportation efficiency, reducing fuel
consumption, and minimizing commute times. While artificial intelligence tools have been …

Accurate, timely, and reliable traffic flow prediction is essential for an intelligent
transportation system due to the complex spatio-temporal correlation of traffic flow. The …

In the power system operational/planning studies, it is a crucial task to provide the load
consumption information in the look‐ahead times. The huge variation of the power system …

With the significant updates of location-acquisition technologies, there are more spatial-
temporal trajectory data available. Spatial-temporal stream plays a crucial role in the …

Very short-term offshore wind speed forecasting by application of Stacked long short-term
memory (LSTM) and Bidirectional LSTM deep learning models is done in this work. Wind …

In literature, various mathematical models have been developed to have a better insight into
the transmission dynamics and control the spread of infectious diseases. Aiming to explore …

Knee osteoporosis (KOP) is a skeletal disorder characterized by bone tissue degradation
and low bone density, leading to a high risk of bone fractures in the knee area. The …

As the core component of rotating machinery, the fault diagnosis of rolling bearing has
important engineering practical significance. Most of the current intelligent fault diagnosis …

In the last 50 years, with the growth of cities and increase in the number of vehicles and
mobility, traffic has become troublesome. As a result, traffic flow prediction started to attract …

Herein, the design optimization of multi-objective controllers for the lateral–directional
motion using proportional–integral–derivative controllers for a twin-engine, propeller-driven …