分数延迟微分方程的高阶数值方法

Manoj Kumar, Aman Jhinga, Varsha Daftardar-Gejji
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引用次数: 0

摘要

在本文中,我们提出了一系列新的高阶数值方法,用于求解非线性分数延迟微分方程(FDDE)并进行误差分析。此外,我们还求解了各种非三维分数延迟微分方程系统,以说明其适用性和实用性。通过使用所提出的数值方法,计算时间大大缩短。这些方法所需的时间仅为分数亚当斯法(FAM)等其他方法的 5%至 10%。此外,这些方法在分数导数值非常小的情况下也能收敛,而 FAM 和 Daftardar-Gejji 等人[1] 提出的新预测器-校正器方法 (NPCM) 却不能收敛。所提方法的收敛阶数是(r+\α \),其中 r 是分数后向差分公式的阶数,\(\α \)表示分数导数的阶数。因此,这些方法比 FAM 或 NPCM 具有更高阶的精度。
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Higher order numerical methods for fractional delay differential equations

In this paper, we present a new family of higher-order numerical methods for solving non-linear fractional delay differential equations (FDDEs) along with the error analysis. Further, we solve various non-trivial systems of FDDEs to illustrate their applicability and utility. By using the proposed numerical methods, computational time is reduced drastically. These methods take only 5 to 10 percent of the time required for other methods such as the fractional Adams method (FAM). Furthermore, these methods converge for very small values of fractional derivative while FAM and the new predictor-corrector method (NPCM) introduced by Daftardar-Gejji et al. [1] do not converge. The order of convergence of the proposed methods is \(r+\alpha \), where r is the order of fractional backward difference formulae and \(\alpha \) denotes the order of the fractional derivative. Thus these methods have a higher order of accuracy than FAM or NPCM.

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