Two-Dimension Nonlinear Optimization Method for Parameter Inversion of Elliptic Equation

2013 ◽  
Vol 347-350 ◽  
pp. 2524-2527
Author(s):  
Yun Qian ◽  
Xiang Guo Liu
Keyword(s):  
Inverse Problem ◽  
Elliptic Equation ◽  
Numerical Simulations ◽  
Numerical Solution ◽  
Nonlinear Optimization ◽  
Linear Optimization ◽  
Optimization Method ◽  
Two Dimensional ◽  
Parameter Inversion ◽  
Parametric Inversion

The paper researches the parametric inversion of the two-dimensional ellipse equation by means of non-linear optimization method, draw a Numerical Solution for such inverse problem. It is shown by numerical simulations that the method is feasible and effective.

The Best Perturbation Method for the Parameter Inversion of Two-Dimension Convection-Diffusion Equation

2013 ◽  
Vol 380-384 ◽  
pp. 1143-1146
Author(s):  
Xiang Guo Liu
Keyword(s):  
Inverse Problem ◽  
Diffusion Equation ◽  
Perturbation Method ◽  
Numerical Simulations ◽  
Numerical Solution ◽  
Two Dimensional ◽  
Convection Diffusion ◽  
Convection Diffusion Equation ◽  
Parameter Inversion ◽  
Parametric Inversion

The paper researches the parametric inversion of the two-dimensional convection-diffusion equation by means of best perturbation method, draw a Numerical Solution for such inverse problem. It is shown by numerical simulations that the method is feasible and effective.

scholarly journals Identification of spacewise dependent right-hand side in two dimensional parabolic equation

2021 ◽  
Vol 2092 (1) ◽  
pp. 012019
Author(s):  
LingDe Su ◽  
V. I. Vasil’ev
Keyword(s):  
Inverse Problem ◽  
Parabolic Equation ◽  
Numerical Solution ◽  
Hand Function ◽  
Adjoint Operator ◽  
Two Dimensional ◽  
Right Hand ◽  
Final Time Point ◽  
The Right ◽  
Constructed Self

Abstract In this paper numerical solution of the inverse problem of determining a spacewise dependent right-hand side function in two dimensional parabolic equation is considered. Usually, the right-hand side function dependent on spatial variable is obtained from measured data of the solution at the final time point. Many mathematical modeling problems in the field of physics and engineering will encounter the inverse problems to identify the right-hand terms. When studying an inverse problem of identifying the spacewise dependent right-hand function, iterative methods are often used. We propose a new conjugate gradient method based on the constructed self-adjoint operator of the equation for numerical solution of the function and numerical examples illustrate the efficiency and accuracy.

Artificial Neural Network Prediction of Deflection Maps for Cable-Driven Robots

2020 ◽  
Author(s):  
Leila Notash
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Nonlinear Optimization ◽  
Linear Optimization ◽  
Optimization Method ◽  
Parallel Robots ◽  
Regression Problem ◽  
Ann Models ◽  
Artificial Neural ◽  
Cable Robots

Abstract In this paper, the learning models of cable-driven robots are developed applying the artificial neural network (ANN). For known input and output data and known relationships (regression problem), the deflection maps of cable-driven parallel robots are predicted utilizing a multi-layer ANN. Two cable robots, a planar robot and a translational spatial robot, are examined to evaluate their models. The deflection maps of these cable robots are generated using the ANN and a non-linear optimization method. The predicted deflections of the ANN models, using much less number of poses for training, are highly satisfactory and comparable to the results obtained by a nonlinear optimization method throughout the pertinent discretized workspaces. In addition, ANN models could predict the deflections for poses that the nonlinear optimization methods may not. Moreover, with variations in robot/task parameters, such as payload, ANN models may predict accurate deflections.

Sign in / Sign up

Export Citation Format

Share Document