Home ›
Entities
› academia
› Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm
Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm
Research article (Reliability Engineering & System Safety, 2023) · cited 32× · AI/ML
Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm
Summary
Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm is a scholarly article[1].
Key Facts
Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm'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). Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm. Retrieved May 24, 2026, from https://4ort.xyz/entity/health-prognostics-of-lithium-ion-batteries-based-on-universal-voltage-range-features-mining-and-adaptive-multi-gaussian
MLA“Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/health-prognostics-of-lithium-ion-batteries-based-on-universal-voltage-range-features-mining-and-adaptive-multi-gaussian.
BibTeX@misc{4ortxyz_health-prognostics-of-lithium-ion-batteries-based-on-universal-voltage-range-features-mining-and-adaptive-multi-gaussian_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm}}, year = {2026}, url = {https://4ort.xyz/entity/health-prognostics-of-lithium-ion-batteries-based-on-universal-voltage-range-features-mining-and-adaptive-multi-gaussian}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Health prognostics of lithium-ion batteries based on universal voltage range features mining and adaptive multi-Gaussian process regression with Harris Hawks optimization algorithm — https://4ort.xyz/entity/health-prognostics-of-lithium-ion-batteries-based-on-universal-voltage-range-features-mining-and-adaptive-multi-gaussian (retrieved 2026-05-24)
