The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery
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Citations
Cites
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Advances in Neural Information Processing Systems 19
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The particle swarm - explosion, stability, and convergence in a multidimensional complex space
Clerc, M., & Kennedy, J. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.985692 · Cited by 9,017
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs
Plett, G. L. (2004) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.02.033 · Cited by 1,768
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Prognostics methods for battery health monitoring using a bayesian framework
Saha, B., Goebel, K., Poll, S., & Christophersen, J. (2009) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2008.2005965 · Cited by 831
Wang, T., Tseng, K. J., Zhao, J., & Wei, Z. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.08.013 · Cited by 713
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Research works printed but not linked: 1
- Poli, 2008, Analysis of the publications on the applications of particle swarm optimization, J Artif Evol Appl, 2008, 10
Cited by
Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review
Li, Y., Liu, K., Foley, A. M., Zülke, A., Berecibar, M., Nanini-Maury, E., Van Mierlo, J., & Hoster, H. E. (2019) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109254 · Cited by 1,193
Big IoT data analytics: Architecture, opportunities, and open research challenges
(2017) · IEEE Access · doi:10.1109/access.2017.2689040 · Cited by 980
A brief review on key technologies in the battery management system of electric vehicles
Liu, K., Li, K., Peng, Q., & Zhang, C. (2019) · Frontiers of Mechanical Engineering · doi:10.1007/s11465-018-0516-8 · Cited by 635
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
Jablonka, K. M., Ongari, D., Moosavi, S. M., & Smit, B. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00004 · Cited by 599
Shen, S., Sadoughi, M., Li, M., Wang, Z., & Hu, C. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.114296 · Cited by 537
Metadata
- Authors
- Hu, C., Jain, G., Zhang, P., Schmidt, C., Gomadam, P., & Gorka, T.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 129
- Pages
- 49-55
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W1998803278
- Cited by
- 302
- References
- 27
- FWCI
- 20.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
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- The paper
- Hu, C., Jain, G., Zhang, P., Schmidt, C., Gomadam, P., & Gorka, T. (2014). Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery. Applied Energy. https://doi.org/10.1016/j.apenergy.2014.04.077
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.
