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A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented.
Our approach is suitable for solving a large class of optimization problems on a rectangle of Rn or unconstrained problems.
Built on these transforms are powerful frameworks and novel techniques for solving a large class of theoretical and industrial problems.
This technique is particularly useful for solving a large class of problems involving discrete-continuous PBEs such as polymerization-depolymerization, aerosol dynamics, etc.
The examples with varying degree of complexities, analyzed here, illustrate its potential for solving a large class of process optimization problems in chemical engineering.
Coupled with the concept of particular solutions and radial basis functions, a simple and effective numerical method for solving a large class of partial differential equations can be achieved.
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It is a general method for the solving a large class of partial differential equations, but is applied to the shallow water equations here.
Actually, the result was extended to more general operators, such as Δ p, under some suitable restrictions in order to solve a large class of problems (see for example the problems considered recently in the work of Covei [44]).
We're working on machines that can be kept around and easily reprogrammed in the lab to solve a large class of problems.
It is shown that this method is very effective and easy and can solve a large class of nonlinear problems.
For future research, we will investigate the relationship between the fuzzy Laplace transform of a fuzzy function and that of its kth derivative, with (kgeq1), then we will apply the Laplace method to solve a large class of FDEs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com