The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
A distributed PSO–SVM hybrid system with feature selection and parameter optimization
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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
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
Cristianini, N., & Shawe-Taylor, J. (2000) · doi:10.1017/cbo9780511801389 · Cited by 13,855
A modified particle swarm optimizer
Shi, Y., & Eberhart, R. (2002) · 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360) · doi:10.1109/icec.1998.699146 · Cited by 10,229
The Nature of Statistical Learning Theory
Sain, S. R. (1996) · Technometrics · doi:10.1080/00401706.1996.10484565 · Cited by 5,434
A discrete binary version of the particle swarm algorithm
Kennedy, J., & Eberhart, R. C. (2002) · 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation · doi:10.1109/icsmc.1997.637339 · Cited by 4,767
Particle swarm optimization: developments, applications and resources
Eberhart, & Shi, Y. (2001) · Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546) · doi:10.1109/cec.2001.934374 · Cited by 4,310
An Introduction to Support Vector Machines
Cristianini, N., & Shawe-Taylor, J. S. (2000) · ePrints Soton (University of Southampton) · Cited by 4,115
UCI Repository of Machine Learning Databases
Murphy, P. M. (1994) · Medical Entomology and Zoology · Cited by 1,844
The Fully Informed Particle Swarm: Simpler, Maybe Better
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Cited by
Particle swarm optimization for feature selection in classification: a multi-objective approach
Xue, B., Zhang, M., & Browne, W. N. (2013) · IEEE Transactions on Cybernetics · doi:10.1109/tsmcb.2012.2227469 · Cited by 1,282
A comprehensive survey on network anomaly detection
Fernandes, G., Rodrigues, J. J. P. C., Carvalho, L. F., Al-Muhtadi, J. F., & Proença, M. L. (2019) · Telecommunication Systems · doi:10.1007/s11235-018-0475-8 · Cited by 382
Pareto front feature selection based on artificial bee colony optimization
Hancer, E., Xue, B., Zhang, M., Karaboga, D., & Akay, B. (2018) · Information Sciences · doi:10.1016/j.ins.2017.09.028 · Cited by 325
An improved particle swarm optimization for feature selection
Liu, Y., Wang, G., Chen, H., Dong, H., Zhu, X., & Wang, S. (2011) · Journal of Bionic Engineering · doi:10.1016/s1672-6529(11)60020-6 · Cited by 324
Metadata
- Authors
- Huang, C.-L., & Dun, J.-F.
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 8
- Issue
- 4
- Pages
- 1381-1391
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2090727353
- Cited by
- 573
- References
- 36
- FWCI
- 11.82
- Type
- journal article
- Language
- en
- Open access
- closed
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- Huang, C.-L., & Dun, J.-F. (2008). A distributed PSO–SVM hybrid system with feature selection and parameter optimization. Applied Soft Computing. https://doi.org/10.1016/j.asoc.2007.10.007
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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.
