Artificial Intelligence
因果引导的局部-全局特征学习
Causality-guided local-global feature learningA machine learning framework that integrates causal inference with deep learning to improve the estimation of Lithium-ion battery State-of-Health (SOH) by utilizing both local and global feature information. / 一种机器学习框架，将因果推断与深度学习相结合，通过利用局部和全局特征信息来提高锂离子电池健康状态（SOH）的估计精度。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-02 22:06:45
Sub-knowledge points
Lithium-ion battery State-of-Health (SOH) estimationCausal inference integrationLocal-global feature fusion
Higher-order knowledge points
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Main parameters and performance indicators
Causality-guided: Mechanism to ensure feature relevanceLocal-global: Strategy to combine fine-grained and high-level featuresSOH: Target variable for battery health estimation
Open problems
No unresolved problem recorded yet
Related literature
ranked by community starsCausality-guided local-global feature learning for lithium-ion battery state-of-health estimationOpen source
Related products and links
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Creation and modification trail
1 recordsRecord title: Causality-guided local-global feature learning.
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