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An equivalent evolutionary (differential) form of the equations is also provided.
The augmented, iterated Kalman smoother is applied to system identification for inverse problems in evolutionary differential equations.
The usefulness and efficiency of some sequential population-based algorithms (electromagnetism-like, particle swarm, evolutionary, differential evolution) as well as a sequential version of the MASA for solving the problem of minimizing the losses in an electric motor have recently been reported in the literature.
In order to state the defining relation for the time-discrete solution and its reformulation as time-discrete variational inequality, we find it useful to focus on the model problem and to utilise an approach via abstract evolutionary differential inclusions, as this resembles the approach for evolution equations exploited in [ 15].
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A new algorithm, called competitive co-evolutionary differential evolution (CODE), is proposed to design analog ICs with practical user-defined specifications.
In this paper, we provide an implementation of a co-evolutionary differential evolution (DE) algorithm in C-CUDA for solving min max problems.
We investigate solution properties of a class of evolutionary partial differential equations (PDEs) with viscous and inviscid regularization.
In order to search for the global optimal solution exactly, one of the evolutionary algorithms, differential evolution (DE) algorithm is employed based on the constructed Kriging surrogate model.
A system of evolutionary partial differential equations (PDEs) describing the two-phase flow of immiscible fluids, such as water gas, through porous media is studied.
It is shown that the CRO outperforms the results of alternative algorithms in this problem, such as Evolutionary Approaches, Differential Evolution or Harmony Search algorithms.
Fractional step Runge Kutta methods are a class of additive Runge Kutta schemes that provide efficient time discretizations for evolutionary partial differential equations.
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