The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
A hybrid particle swarm optimization algorithm using adaptive learning strategy
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Citations
Cites
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Empirical study of particle swarm optimization
Shi, Y., & Eberhart, R. C. (2003) · Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406) · doi:10.1109/cec.1999.785511 · Cited by 3,945
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
Liang, J. J., Qin, A. K., Suganthan, P. N., & Baskar, S. (2006) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2005.857610 · Cited by 3,743
Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients
Ratnaweera, A., Halgamuge, S. K., & Watson, H. C. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826071 · Cited by 3,034
Adaptive Particle Swarm Optimization
Zhan, Z.-H., Zhang, J., Li, Y., & Chung, H. S.-H. (2009) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2009.2015956 · Cited by 2,075
Population structure and particle swarm performance
Kennedy, J., & Mendes, R. (2003) · Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600) · doi:10.1109/cec.2002.1004493 · Cited by 1,586
Proceedings Congress on Evolutionary Computation 2001
(2001) · Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat No 01TH8546) CEC-01 · doi:10.1109/cec.2001.934259 · Cited by 1,086
A Competitive Swarm Optimizer for Large Scale Optimization
Cheng, R., & Jin, Y. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2322602 · Cited by 1,052
Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization
Chatterjee, A., & Siarry, P. (2006) · Computers & Operations Research · doi:10.1016/j.cor.2004.08.012 · Cited by 690
Liang, J., Qu, B., Suganthan, P. N., et al. (2013) · Cited by 688
Cited by
Particle Swarm Optimization: A Comprehensive Survey
Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022) · IEEE Access · doi:10.1109/access.2022.3142859 · Cited by 1,584
Metadata
- Authors
- Wang, F., Zhang, H., Li, K., Lin, Z., Yang, J., & Shen, X.-L.
- Venue
- Information Sciences
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 436-437
- Pages
- 162-177
- ISSN
- 0020-0255 (ISSN-L)
- OpenAlex
- W2790368141
- Cited by
- 284
- References
- 26
- FWCI
- 20.79
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, F., Zhang, H., Li, K., Lin, Z., Yang, J., & Shen, X.-L. (2018). A hybrid particle swarm optimization algorithm using adaptive learning strategy. Information Sciences. https://doi.org/10.1016/j.ins.2018.01.027
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.
