Home ›
Entities
› academia
› An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries
An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries
Research article (Journal of Energy Storage, 2024) · cited 52× · AI/ML
An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries
Summary
An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries is a scholarly article[1].
Key Facts
An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-improved-convolutional-neural-network-bidirectional-gated-recurrent-unit-algorithm-for-robust-state-of-charge-and-sta
MLA“An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-improved-convolutional-neural-network-bidirectional-gated-recurrent-unit-algorithm-for-robust-state-of-charge-and-sta.
BibTeX@misc{4ortxyz_an-improved-convolutional-neural-network-bidirectional-gated-recurrent-unit-algorithm-for-robust-state-of-charge-and-sta_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries}}, year = {2026}, url = {https://4ort.xyz/entity/an-improved-convolutional-neural-network-bidirectional-gated-recurrent-unit-algorithm-for-robust-state-of-charge-and-sta}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An improved convolutional neural network-bidirectional gated recurrent unit algorithm for robust state of charge and state of energy estimation of new energy vehicles of lithium-ion batteries — https://4ort.xyz/entity/an-improved-convolutional-neural-network-bidirectional-gated-recurrent-unit-algorithm-for-robust-state-of-charge-and-sta (retrieved 2026-05-24)
