IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v38y2001i2p161-180.html
   My bibliography  Save this article

Extending the Kohonen self-organizing map networks for clustering analysis

Author

Listed:
  • Kiang, Melody Y.

Abstract

No abstract is available for this item.

Suggested Citation

  • Kiang, Melody Y., 2001. "Extending the Kohonen self-organizing map networks for clustering analysis," Computational Statistics & Data Analysis, Elsevier, vol. 38(2), pages 161-180, December.
    • Handle: RePEc:eee:csdana:v:38:y:2001:i:2:p:161-180
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(01)00040-8
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kulkarni, Uday R. & Kiang, Melody Y., 1995. "Dynamic grouping of parts in flexible manufacturing systems -- a self-organizing neural networks approach," European Journal of Operational Research, Elsevier, vol. 84(1), pages 192-212, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Li-Ching, 2010. "Visualizing preferences on spheres for group decisions based on multiplicative preference relations," European Journal of Operational Research, Elsevier, vol. 203(1), pages 176-184, May.
    2. Kiang, Melody Y. & Hu, Michael Y. & Fisher, Dorothy M., 2007. "The effect of sample size on the extended self-organizing map network--A market segmentation application," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5940-5948, August.
    3. Alejandro Blanco-M. & Karina Gibert & Pere Marti-Puig & Jordi Cusidó & Jordi Solé-Casals, 2018. "Identifying Health Status of Wind Turbines by Using Self Organizing Maps and Interpretation-Oriented Post-Processing Tools," Energies, MDPI, vol. 11(4), pages 1-21, March.
    4. Qianyu Gao & Guofang Li & Jin Bao & Jian Wang, 2021. "Regional Frequency Analysis Based on Precipitation Regionalization Accounting for Temporal Variability and a Nonstationary Index Flood Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4435-4456, October.
    5. Jach Agnieszka E & Marín Juan M, 2010. "Classification of Genomic Sequences via Wavelet Variance and a Self-Organizing Map with an Application to Mitochondrial DNA," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-14, July.
    6. Mingoti, Sueli A. & Lima, Joab O., 2006. "Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1742-1759, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohamed, Zubair M. & Kumar, Ashok & Motwani, Jaideep, 1999. "An improved part grouping model for minimizing makespan in FMS," European Journal of Operational Research, Elsevier, vol. 116(1), pages 171-182, July.
    2. Shouhong Wang, 2001. "Cluster analysis using a validated self‐organizing method: cases of problem identification," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(2), pages 127-138, June.
    3. Yin, Yong & Yasuda, Kazuhiko, 2006. "Similarity coefficient methods applied to the cell formation problem: A taxonomy and review," International Journal of Production Economics, Elsevier, vol. 101(2), pages 329-352, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:38:y:2001:i:2:p:161-180. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.