Artificial Intelligence
物理信息深度学习
Physics-informed deep learningA machine learning framework that integrates physical laws and constraints into the neural network training process to improve prediction accuracy and generalization, particularly for systems with sparse data. / 一种将物理定律和约束集成到神经网络训练过程中的机器学习框架，以提高预测精度和泛化能力，特别是针对稀疏数据系统。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-10-31 23:05:55
Sub-knowledge points
Higher-order knowledge points
Deep Learning / 工艺技术Scientific computing
Main parameters and performance indicators
physics-informed loss function: combines data-driven loss with physics-based residualssparse observation: limited or irregular input data points
Open problems
No unresolved problem recorded yet
Related literature
ranked by community starsN-PCLN: A physics-informed deep learning framework for short-term chlorophyll-a prediction with sparse satellite observationOpen source
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Creation and modification trail
1 recordsRecord title: Physics-informed deep learning.
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