Data-driven seismic response prediction of structural components
H Luo, SG Paal - Earthquake Spectra, 2022 - journals.sagepub.com
Lateral stiffness of structural components, such as reinforced concrete (RC) columns, plays
an important role in resisting the lateral earthquake loads. The lateral stiffness relates the …
an important role in resisting the lateral earthquake loads. The lateral stiffness relates the …
The application of neural networks to the modeling of magnetic hysteresis
N Vuokila, C Cunning, J Zhang, N Akel… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Accurately modeling magnetic hysteresis plays a crucial role in developing precise digital
twins for low-frequency electromagnetic systems. However, in large 3-D analysis systems …
twins for low-frequency electromagnetic systems. However, in large 3-D analysis systems …
Application of least-squares support-vector machine based on hysteresis operators and particle swarm optimization for modeling and control of hysteresis in …
AG Baziyad, AS Nouh, I Ahmad, A Alkuhayli - Actuators, 2022 - mdpi.com
Nanopositioning systems driven by piezoelectric actuators are widely used in different fields.
However, the hysteresis phenomenon is a major factor in reducing the positioning accuracy …
However, the hysteresis phenomenon is a major factor in reducing the positioning accuracy …
Hysteresis identification using extended preisach neural network
Hysteresis phenomena have been observed in different branches of physics and
engineering sciences. Therefore several models have been proposed for hysteresis …
engineering sciences. Therefore several models have been proposed for hysteresis …
Modeling hysteretic deteriorating behavior using generalized Prandtl neural network
In this paper, a new kind of activation function using a particular combination of stop and
play operators is proposed and used in a feedforward neural network to improve its learning …
play operators is proposed and used in a feedforward neural network to improve its learning …
Hysteresis simulation using least-squares support vector machine
M Farrokh - Journal of Engineering Mechanics, 2018 - ascelibrary.org
Hysteresis is a highly nonlinear phenomenon, which is observed in different branches of
sciences. The behavior of the hysteretic systems is usually controlled by some …
sciences. The behavior of the hysteretic systems is usually controlled by some …
An Extreme Learning Machine for the Simulation of Different Hysteretic Behaviors
Hysteresis is a non− unique phenomenon known as a multi− valued mapping in different
fields of science and engineering. Accurate identification of the hysteretic systems is a …
fields of science and engineering. Accurate identification of the hysteretic systems is a …
Adaptive simulation of hysteresis using neuro-Madelung model
Hysteretic phenomena have been observed in different branches of engineering sciences.
Although each of them has its own characteristics, Madelung's rules are common among …
Although each of them has its own characteristics, Madelung's rules are common among …
Universal hysteresis identification using extended Preisach neural network
Hysteresis phenomena have been observed in different branches of physics and
engineering sciences. Therefore, several models have been proposed for hysteresis …
engineering sciences. Therefore, several models have been proposed for hysteresis …
[PDF][PDF] Nonlinear adaptive simulation of concrete gravity dams using generalized prandtl neural networks
Generalized Prandtl Neural Networks (GPNNs) has been used in Nonlinear Dynamic
analysis of concrete gravity dams. GPNNs are the new type of neural networks, by which …
analysis of concrete gravity dams. GPNNs are the new type of neural networks, by which …