Abstract Machine learning (ML) methods has recently contributed very well in the
advancement of the prediction models used for energy consumption. Such models highly …

The control strategy insures the efficiency, increased production and safety in new and
complicated energy conversion systems. To this end, a thermodynamic model that simulates …

Although convolutional neural networks (CNNs) can be used to classify electrocardiogram
(ECG) beats in the diagnosis of cardiovascular disease, ECG signals are typically processed …

Effective reduction of micro-amplitude vibration has always been a serious challenge. The
nonlinear energy sink (NES) has been proven to be able to reduce vibration at a wide …

To improve the maneuverability and stability of a vehicle and fully leverage the advantages
of torque vectoring technology in vehicle dynamics control, a finite-time yaw rate and …

The main goal of this article is to provide parameterization study for vibration behavior of
functionally graded porous (FGP) doubly-curved panels and shells of revolution by using a …

The demand of accurate and real-time dynamics model has recently become critical for
implementing effective vibration control in vehicles. The multibody dynamics method …

With the increase in speed of high-speed trains, their vibration will become fiercer and
fiercer, especially when the lateral resonance of the car body occurs. This paper develops a …

In this paper, a novel three-dimensional exact solution is performed for vibration analysis of
thick functionally graded porous rectangular plates subject to arbitrary boundary conditions …

A vibration isolator based on a tunable negative stiffness mechanism combines the
advantages of high-static-low-dynamic stiffness (HSLDS) isolators to expand the isolation …