applied mathematics
有界分数阶物理信息神经网络
Tempered Fractional Physics-Informed Neural NetworkA numerical method combining tempered fractional calculus with physics-informed neural networks to solve nonlinear tempered time-fractional subdiffusion equations / 一种结合有界分数阶微积分与物理信息神经网络的数值方法，用于求解非线性有界时间分数阶次扩散方程。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-10-24 19:01:47
Sub-knowledge points
Forward problem solvingInverse problem solving
Higher-order knowledge points
Main parameters and performance indicators
Tempered fractional order: Controls the decay rate of the kernelTime-fractional order: Determines the anomalous diffusion behaviorPhysics-informed loss: Enforces governing equations and boundary conditions
Open problems
No unresolved problem recorded yet
Related literature
ranked by community starsFast tempered fractional physics-informed neural network for nonlinear tempered time-fractional subdiffusion equations: Forward and inverse problemsOpen source
Related products and links
No item recorded yet
Creation and modification trail
1 recordsRecord title: Tempered Fractional Physics-Informed Neural Network.
Node update feedback
review required