2014
DOI: 10.1007/s10910-014-0363-8
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A new efficient technique for solving two-point boundary value problems for integro-differential equations

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Cited by 6 publications
(3 citation statements)
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“…Many problems in chemical engineering are described by means of ordinary differential equations or partial differential equations with initial or boundary conditions [19,20]. In the numerical section, we transform, by means of divided differences, a nonlinear boundary value problem with non-Dirichlet conditions in a nonlinear system, whose solution is an approximation of the solution of the boundary value problem in a set of discrete points of the domain.…”
Section: Introductionmentioning
confidence: 99%
“…Many problems in chemical engineering are described by means of ordinary differential equations or partial differential equations with initial or boundary conditions [19,20]. In the numerical section, we transform, by means of divided differences, a nonlinear boundary value problem with non-Dirichlet conditions in a nonlinear system, whose solution is an approximation of the solution of the boundary value problem in a set of discrete points of the domain.…”
Section: Introductionmentioning
confidence: 99%
“…In many branches of applied mathematics, chemistry, physics and engineering, efficient solvers of nonlinear problems are needed: in mass and heat transfer within porous catalyst particles, some boundary value problems for integro-differential equations appear that, after accurate discretization, Adomian decomposition or other techniques, yield to a nonlinear system of equations (see, for example [1] and [2]). Also nonlinear reactiondiffusion equations arise in autocatalytic chemical reactions (see [3]) or the analysis of the electronic structure of the hydrogen-atom in strong magnetic fields can be treated numerically, [4], by using iterative procedures for solving nonlinear problems.…”
Section: Introductionmentioning
confidence: 99%
“…Comparison of the absolute error of Example 4.1 by using new method and modified ADM decomposition method in the paper[7] 表 1. 模型(4.1)中用新方法和改进的 ADM 分解方法得到的绝对误差比较[7] …”
mentioning
confidence: 99%