The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries
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Cites
Liu, K., Shang, Y., Ouyang, Q., & Widanage, W. D. (2021) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2020.2973876 · Cited by 833
A Data-Driven Auto-CNN-LSTM Prediction Model for Lithium-Ion Battery Remaining Useful Life
Ren, L., Dong, J., Wang, X., Meng, Z., Zhao, L., & Deen, M. J. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3008223 · Cited by 690
Li, P., Zhang, Z., Xiong, Q., Ding, B., Hou, J., Luo, D., Rong, Y., & Li, S. (2020) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.228069 · Cited by 457
Hossain Lipu, M. S., Hannan, M. A., Karim, T. F., Hussain, A., Saad, M. H. M., Ayob, A., Miah, M. S., & Indra Mahlia, T. M. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.126044 · Cited by 446
Online capacity estimation of lithium-ion batteries with deep long short-term memory networks
Li, W., Sengupta, N., Dechent, P., Howey, D., Annaswamy, A., & Sauer, D. U. (2021) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.228863 · Cited by 362
Lian, R., Peng, J., Wu, Y., Tan, H., & Zhang, H. (2020) · Energy · doi:10.1016/j.energy.2020.117297 · Cited by 357
Ma, Y., Shan, C., Gao, J., & Chen, H. (2022) · Energy · doi:10.1016/j.energy.2022.123973 · Cited by 351
Remaining Useful Life Assessment for Lithium-Ion Batteries Using CNN-LSTM-DNN Hybrid Method
Zraibi, B., Okar, C., Chaoui, H., & Mansouri, M. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3071622 · Cited by 321
A hybrid statistical data-driven method for on-line joint state estimation of lithium-ion batteries
Song, Y., Liu, D., Liao, H., & Peng, Y. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.114408 · Cited by 266
Khodadadi Sadabadi, K., Jin, X., & Rizzoni, G. (2021) · Journal of Power Sources · doi:10.1016/j.jpowsour.2020.228861 · Cited by 266
Cited by
Wang, S., Wu, F., Takyi-Aninakwa, P., Fernandez, C., Stroe, D.-I., & Huang, Q. (2023) · Energy · doi:10.1016/j.energy.2023.128677 · Cited by 281
Self-citationState of charge estimation for electric vehicles using random forest
Sulaiman, M. H., & Mustaffa, Z. (2024) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2024.100177 · Cited by 102
Kim, J., Sin, S., & Kim, J. (2024) · Energy · doi:10.1016/j.energy.2024.131285 · Cited by 50
Qian, L., Xuan, L., & Chen, J. (2023) · Frontiers in Energy Research · doi:10.3389/fenrg.2023.1218580 · Cited by 38
Alonso-Villar, A., Davíðsdóttir, B., Stefánsson, H., Ásgeirsson, E. I., & Kristjánsson, R. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.137997 · Cited by 30
Metadata
- Authors
- Wang, S., Fan, Y., Jin, S., Takyi-Aninakwa, P., & Fernandez, C.
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2023-02
- Volume
- 230
- Pages
- 108920
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W4307897928
- Cited by
- 554
- References
- 52
- FWCI
- 30.12
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries. https://app.cochat.ai/papers/10.1016/j.ress.2022.108920
- The paper
- Wang, S., Fan, Y., Jin, S., Takyi-Aninakwa, P., & Fernandez, C. (2023). Improved anti-noise adaptive long short-term memory neural network modeling for the robust remaining useful life prediction of lithium-ion batteries. Reliability Engineering & System Safety. https://doi.org/10.1016/j.ress.2022.108920
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
