Attention-based BILSTM for the degradation trend prediction of lithium battery

Research article (Energy Reports, 2023) · cited 22× · AI/ML
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Attention-based BILSTM for the degradation trend prediction of lithium battery

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Attention-based BILSTM for the degradation trend prediction of lithium battery is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Attention-based BILSTM for the degradation trend prediction of lithium battery. Retrieved May 24, 2026, from https://4ort.xyz/entity/attention-based-bilstm-for-the-degradation-trend-prediction-of-lithium-battery
MLA “Attention-based BILSTM for the degradation trend prediction of lithium battery.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/attention-based-bilstm-for-the-degradation-trend-prediction-of-lithium-battery.
BibTeX @misc{4ortxyz_attention-based-bilstm-for-the-degradation-trend-prediction-of-lithium-battery_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Attention-based BILSTM for the degradation trend prediction of lithium battery}}, year = {2026}, url = {https://4ort.xyz/entity/attention-based-bilstm-for-the-degradation-trend-prediction-of-lithium-battery}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Attention-based BILSTM for the degradation trend prediction of lithium battery — https://4ort.xyz/entity/attention-based-bilstm-for-the-degradation-trend-prediction-of-lithium-battery (retrieved 2026-05-24)

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