Home ›
Entities
› academia
› Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads
Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads
Research article (Journal of Energy Storage, 2021) · cited 43× · AI/ML
Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads
Summary
Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads is a scholarly article[1].
Key Facts
Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads'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). Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads. Retrieved May 24, 2026, from https://4ort.xyz/entity/investigation-of-the-performance-of-direct-forecasting-strategy-using-machine-learning-in-state-of-charge-prediction-of-
MLA“Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/investigation-of-the-performance-of-direct-forecasting-strategy-using-machine-learning-in-state-of-charge-prediction-of-.
BibTeX@misc{4ortxyz_investigation-of-the-performance-of-direct-forecasting-strategy-using-machine-learning-in-state-of-charge-prediction-of-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads}}, year = {2026}, url = {https://4ort.xyz/entity/investigation-of-the-performance-of-direct-forecasting-strategy-using-machine-learning-in-state-of-charge-prediction-of-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Investigation of the performance of direct forecasting strategy using machine learning in State-of-Charge prediction of Li-ion batteries exposed to dynamic loads — https://4ort.xyz/entity/investigation-of-the-performance-of-direct-forecasting-strategy-using-machine-learning-in-state-of-charge-prediction-of- (retrieved 2026-05-24)