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Numerical methods for space-fractional diffusion equations often generate dense or even full stiffness matrices.
In this paper, we have introduced a combination of perturbation and Laplace methods for space-time fractional problem which we called the PLM.
Because of the non-local property of fractional differential operators, numerical methods for space-fractional diffusion equations generate dense or even full coefficient matrices with complicated structures.
Because of the nonlocal property of fractional differential operators, numerical methods for space-fractional diffusion equations generate dense or even full coefficient matrices with complicated structures.
The main existing inverse solution method for space robot includes analytical method, geometric method, numerical methods and neural network method.
The explicit finite element method for transient dynamics of linear elasticity is formulated by using Galerkin method for space and the central difference method for time.
Dehghan et al. [15] used a finite difference scheme for Riemann-Liouville fractional derivative and the Legendre spectral element method for space component.
The main purpose of this paper is to present a pretension design method for space deployable mesh reflectors under multi-uncertainty.
Our approach hinges on the following essential features: shape differential calculus, a semi-implicit time discretization and a finite element method for space discretization.
Then combining with the anti-optimization strategy, a pretension design method for space deployable mesh reflectors considering multi-uncertainty is proposed to minimize the influence from the uncertainties.
This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks.
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