人工神经网络
梯度下降
分数阶微积分
平衡流
能量(信号处理)
功能(生物学)
计算机科学
应用数学
图层(电子)
数学
激活函数
扩散
算法
数学分析
人工智能
物理
统计
化学
有机化学
进化生物学
生物
热力学
作者
Babak Shiri,Hua Kong,Guo–Cheng Wu,Cheng Luo
摘要
A neural network method for solving fractional diffusion equations is presented in this letter. An adaptive gradient descent method is proposed to minimize energy functions. Due to the memory effects of the fractional calculus, the gradient of energy function becomes much more complicated, and we suggest a simplified method. Numerical examples with one-layer and two-layer neurons show the effectiveness of the method.
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