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An Hybrid Approach for Data Clustering Using K-Means and Teaching Learning Based Optimization

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Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India CSI Volume 2

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 338))

Abstract

A new efficient method for optimization, ‘Teaching-Learning Based Optimization (TLBO)’, has been proposed very recently for addressing the mechanical design problems and it can also be used for clustering numerical data. In this paper teaching learning based optimization is used along with kmeans algorithm for clustering the data into user specified number of clusters. It shows how TLBO can be used to find the centroids of a user specified number of clusters. The hybrid algorithm has been implemented for attaining better results for clustering.

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Author information

Authors and Affiliations

  1. Anil Neerukonda Institute of Technology and Sciences, Visakapatnam, India

    Pavan Kumar Mummareddy & Suresh Chandra Satapaty

Authors
  1. Pavan Kumar Mummareddy
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  2. Suresh Chandra Satapaty
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Corresponding author

Correspondence to Pavan Kumar Mummareddy .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  2. School of Information Technology, Jawaharlal Nehru Technological University Hyderabad, Hyderabad, India

    A. Govardhan

  3. Department of CSE, Computer Society of India, Hyderabad, India

    K. Srujan Raju

  4. University of Kalyanai, Kalyanai, West Bengal, India

    J. K. Mandal

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© 2015 Springer International Publishing Switzerland

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Mummareddy, P.K., Satapaty, S.C. (2015). An Hybrid Approach for Data Clustering Using K-Means and Teaching Learning Based Optimization. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India CSI Volume 2. Advances in Intelligent Systems and Computing, vol 338. Springer, Cham. https://doi.org/10.1007/978-3-319-13731-5_19

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  • DOI: https://doi.org/10.1007/978-3-319-13731-5_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13730-8

  • Online ISBN: 978-3-319-13731-5

  • eBook Packages: EngineeringEngineering (R0)

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