Remaining Useful Life Prediction for Lithium-Ion Batteries Based on a Deep Mixed-Effect Gaussian Process Model

Jiayu Shi, Zebiao Feng

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DOI: 10.3390/math14091408
Published: 2026-04-22
Container: Mathematics
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/math14091408,
  title = {Remaining Useful Life Prediction for Lithium-Ion Batteries Based on a Deep Mixed-Effect Gaussian Process Model},
  author = {Jiayu Shi and Zebiao Feng},
  year = {2026},
  journal = {Mathematics},
  doi = {10.3390/math14091408},
  url = {https://doi.org/10.3390/math14091408}
}

RIS

TY  - JOUR
TI  - Remaining Useful Life Prediction for Lithium-Ion Batteries Based on a Deep Mixed-Effect Gaussian Process Model
AU  - Jiayu Shi
AU  - Zebiao Feng
PY  - 2026
JO  - Mathematics
DO  - 10.3390/math14091408
UR  - https://doi.org/10.3390/math14091408
ER  -

APA

Shi, J., & Feng, Z. (2026). Remaining Useful Life Prediction for Lithium-Ion Batteries Based on a Deep Mixed-Effect Gaussian Process Model. Mathematics. https://doi.org/10.3390/math14091408

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crossref · retrieved 2026-09-26T19:04:13.614Z