In this work, a methodology based on a neural network to solve fractal-fractional differential equations with a nonsingular and nonlocal kernel is proposed, the neural network is optimized by the Levenberg–Marquardt algorithm. For evaluating the neural network, different chaotic oscillators of variable order are solved and compared with algorithms of numeric approximation.

中文翻译：

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使用人工神经网络的变阶分形-分数 Mittag-Leffler 微分方程的数值解

在这项工作中，提出了一种基于神经网络的方法来求解具有非奇异和非局部核的分形分数微分方程，神经网络通过 Levenberg-Marquardt 算法进行优化。为了评估神经网络，解决了不同阶数的混沌振荡器，并与数值逼近算法进行了比较。