Computational Science and Engineering
物理信息伴随神经网络
Physics-informed adjoint neural networkA neural network architecture that integrates physical laws (PDEs) into the loss function to solve parametric Partial Differential Equation (PDE)-constrained optimal control problems. / 一种将物理定律（偏微分方程）集成到损失函数中以求解参数化偏微分方程约束最优控制问题的神经网络架构。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-08 22:06:59
Sub-knowledge points
Adjoint-based gradient computationParametric PDE solvingOptimal control optimization
Higher-order knowledge points
Main parameters and performance indicators
PDE constraints: Governing equations of the physical systemOptimal control variables: Parameters to be optimizedAdjoint method: Mathematical technique for sensitivity analysis
Open problems
No unresolved problem recorded yet
Related literature
ranked by community starsPhysics-informed adjoint neural network for parametric PDE-constrained optimal control problemsOpen source
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1 recordsRecord title: Physics-informed adjoint neural network.
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