Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Error Analysis and Model Efficiency for the Jaulent-Miodek System Using Physics-Informed Neural Networks
View through CrossRef
This paper focuses on approximate solution of the Jaulent-Miodek system, which is a nonlinear-coupledpartial differential equations. Physics-Informed Neural Network (PINN) architecture is implemented tofind an approximate solution against the independent variables. Loss function is defined using PDEs andinitial conditions. The PINN is set up to meet both the governing PDEs and the starting conditions.It does this by using automated differentiation to enforce the system’s residuals in the loss function.The results is compared with the exact solution using graphical representations. The model is tested forspecific values of ψ. The error is illustrated in table, which shows the model efficiency and accuracy.
Title: Error Analysis and Model Efficiency for the Jaulent-Miodek System Using Physics-Informed Neural Networks
Description:
This paper focuses on approximate solution of the Jaulent-Miodek system, which is a nonlinear-coupledpartial differential equations.
Physics-Informed Neural Network (PINN) architecture is implemented tofind an approximate solution against the independent variables.
Loss function is defined using PDEs andinitial conditions.
The PINN is set up to meet both the governing PDEs and the starting conditions.
It does this by using automated differentiation to enforce the system’s residuals in the loss function.
The results is compared with the exact solution using graphical representations.
The model is tested forspecific values of ψ.
The error is illustrated in table, which shows the model efficiency and accuracy.
Related Results
Explicit Exact Solutions of the (2+1)-Dimensional Integro-Differential Jaulent–Miodek Evolution Equation Using the Reliable Methods
Explicit Exact Solutions of the (2+1)-Dimensional Integro-Differential Jaulent–Miodek Evolution Equation Using the Reliable Methods
In this article, we utilize the G′/G2-expansion method and the Jacobi elliptic equation method to analytically solve the (2 + 1)-dimensional integro-differential Jaulent–Miodek equ...
Fuzzy Chaotic Neural Networks
Fuzzy Chaotic Neural Networks
An understanding of the human brain’s local function has improved in recent years. But the cognition of human brain’s working process as a whole is still obscure. Both fuzzy logic ...
On the role of network dynamics for information processing in artificial and biological neural networks
On the role of network dynamics for information processing in artificial and biological neural networks
Understanding how interactions in complex systems give rise to various collective behaviours has been of interest for researchers across a wide range of fields. However, despite ma...
NON-CLASSICAL LIE SYMMETRY ANALYSIS OF KDV, JAULENT–MIODEK, AND JIMBO–MIWA EQUATIONS
NON-CLASSICAL LIE SYMMETRY ANALYSIS OF KDV, JAULENT–MIODEK, AND JIMBO–MIWA EQUATIONS
The Lie symmetry analysis of non-classical is presented in the context of three important nonlinear partial differential equations, the (1+1)-dimensional Kortewegde Vries (KdV) equ...
NICU Medication Errors: Describing the Cause and Nature of Medication Errors in a NICU in Qatar
NICU Medication Errors: Describing the Cause and Nature of Medication Errors in a NICU in Qatar
IntroductionA medication error can be defined as “any error occurring in the medication use process” and focuses on problems with the delivery of medication to a patient [1]. Medic...
ACM SIGCOMM computer communication review
ACM SIGCOMM computer communication review
At some point in the future, how far out we do not exactly know, wireless access to the Internet will outstrip all other forms of access bringing the freedom of mobility to the way...
Memorization capacity and robustness of neural networks
Memorization capacity and robustness of neural networks
Machine learning, and deep learning in particular, has recently undergone rapid advancements. To contribute to a rigorous understanding of deep learning, this thesis explores two d...
Artificial neural network for the recognition of human emotions under a backpropagation algorithm
Artificial neural network for the recognition of human emotions under a backpropagation algorithm
The era of the technological revolution increasingly encourages the development of technologies that facilitate in one way or another people's daily activities, thus generating a g...