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Computational Optimization of Residual Power Series Algorithm for Certain Classes of Fuzzy Fractional Differential Equations

机译:一类模糊分数阶微分方程的剩余幂级数算法的计算优化

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This paper aims to present a novel optimization technique, the residual power series (RPS), for handling certain classes of fuzzy fractional differential equations of order under strongly generalized differentiability. The proposed technique relies on generalized Taylor formula under Caputo sense aiming at extracting a supportive analytical solution in convergent series form. The RPS algorithm is significant and straightforward tool for creating a fractional power series solution without linearization, limitation on the problem’s nature, sort of classification, or perturbation. Some illustrative examples are provided to demonstrate the feasibility of the RPS scheme. The results obtained show that the scheme is simple and reliable and there is good agreement with exact solution.
机译:本文旨在提出一种新的优化技术,即残差幂级数(RPS),用于在强广义可微性下处理某些类别的模糊分数阶微分方程。所提出的技术依赖于Caputo意义下的广义泰勒公式,旨在提取收敛级数形式的支持性解析解。 RPS算法是一种重要的直接工具,可用于创建分数次幂级数解决方案,而无需进行线性化,问题性质,类别分类或扰动限制。提供了一些说明性示例以证明RPS方案的可行性。结果表明,该方案简单可靠,与精确解具有良好的一致性。

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