For solving numerically fractional differential equations, we have to take into account a rising flow of works as (Dehestani et al. in Appl Math Comput 336:433–453, 2018, https://doi.org/10.1016/j.amc.2018.05.017, Rahimkhani et al. Appl Math Model 40:8087–8107, 2016, https://doi.org/10.1016/j.apm.2016.04.026) that show the advantage of using the transformation \(x \rightarrow x^\alpha \). In this paper, we aim to explain this transformation, and using the acquired knowledge, we are also discussing a method that is able to improve the accuracy of the numerical results for the delay fractional equations. We conclude the paper with two numerical examples to illustrate the analysis of this paper.

为了求解数值分数微分方程，我们必须考虑到工作量的增加（Dehestani 等人在 Appl Math Comput 336:433–453, 2018, https://doi.org/10.1016/j.amc。 2018.05.017, Rahimkhani et al. Appl Math Model 40:8087–8107, 2016, https://doi.org/10.1016/j.apm.2016.04.026) 展示了使用转换\(x \rightarrow x^\alpha \)。在本文中，我们旨在解释这种变换，并利用所获得的知识，我们还讨论了一种能够提高延迟分数方程数值结果准确性的方法。我们用两个数值例子来结束本文，以说明本文的分析。