The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
A Simplex Method for Function Minimization
Nelder, J. A., & Mead, R. (1965) · The Computer Journal · doi:10.1093/comjnl/7.4.308 · Cited by 28,905
Data mining: concepts and techniques
(2012) · Choice Reviews Online · doi:10.5860/choice.49-3305 · Cited by 28,531
Indexing by latent semantic analysis
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990) · Journal of the American Society for Information Science · doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9 · Cited by 12,751
A tutorial on spectral clustering
von Luxburg, U. (2007) · Statistics and Computing · doi:10.1007/s11222-007-9033-z · Cited by 10,349
Finding Groups in Data: An Introduction to Cluster Analysis
Kaufman, L., & Rousseeuw, P. J. (1990) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316801 · Cited by 7,344 · cited 2×
“The PSO algorithm was compared to Partitioning Around Medoids (PAM) (Kaufman and Rousseeauw 1990) and in terms of efficiency; PSO efficiency was superior.”
(2008) · Data Mining and Market Intelligence for Optimal Marketing Returns · doi:10.4324/9780080878096-12 · Cited by 6,954
Data Mining - Concepts and Techniques.
Perner, P. (2002) · Künstliche Intell. · Cited by 4,886
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
An Introduction to Data Mining
Stephens, C. R., & Sukumar, R. (2006) · The Handbook of Marketing Research · doi:10.4135/9781412973380.n22 · Cited by 4,562
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
Decision Making in Multiagent Systems: A Survey
Rizk, Y., Awad, M., & Tunstel, E. W. (2018) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2018.2840971 · Cited by 219
Study on optimizing production scheduling for water-saving in textile dyeing industry
Zhou, L., Xu, K., Cheng, X., Xu, Y., & Jia, Q. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.09.047 · Cited by 62
Swarm Intelligence Techniques in Recommender Systems-a Review of Recent Research
Peška, L., Tashu, T. M., & Horváth, T. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2019.04.003 · Cited by 54
Wu, G., Peng, W., Hu, X., Wang, R., & Chen, H. (2020) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2020.100690 · Cited by 13
Metadata
- Authors
- Esmin, A. A. A., Coelho, R. A., & Matwin, S.
- Venue
- Artificial Intelligence Review
- Published
- 2013-02-15
- Volume
- 44
- Issue
- 1
- Pages
- 23-45
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W2094521916
- Cited by
- 340
- References
- 79
- FWCI
- 15.83
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data. https://app.cochat.ai/papers/10.1007/s10462-013-9400-4
- The paper
- Esmin, A. A. A., Coelho, R. A., & Matwin, S. (2015). A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data. Artificial Intelligence Review. https://doi.org/10.1007/s10462-013-9400-4
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.
