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A Framework of Clustering Based on Chicken Swarm Optimization

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Recent Advances on Soft Computing and Data Mining (SCDM 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 549))

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Abstract

Chicken Swarm Optimization (CSO) algorithm which is one of the most recently introduced optimization algorithms, simulates the intelligent foraging behaviour of chicken swarm. Data clustering is used in many disciplines and applications. It is an important tool and a descriptive task seeking to identify homogeneous groups of objects based on the values of their attributes. In this work, CSO is used for data clustering. The performance of the proposed CSO was assessed on several data sets and compared with well known and recent metaheuristic algorithm for clustering: Particle Swarm Optimization (PSO) algorithm, Cuckoo Search (CS) and Bee Colony Algorithm (BC). The simulation results indicate that CSO algorithm have much potential and can efficiently be used for data clustering.

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Author information

Authors and Affiliations

  1. Mathematics Department, Universitas Ahmad Dahlan, Yogyakarta, Indonesia

    Nursyiva Irsalinda

  2. Information System Department, Universitas Ahmad Dahlan, Yogyakarta, Indonesia

    Iwan Tri Riyadi Yanto

  3. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Haruna Chiroma & Tutut Herawan

Authors
  1. Nursyiva Irsalinda
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  2. Iwan Tri Riyadi Yanto
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  3. Haruna Chiroma
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  4. Tutut Herawan
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Corresponding author

Correspondence to Nursyiva Irsalinda .

Editor information

Editors and Affiliations

  1. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Rozaida Ghazali

  3. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Nazri Mohd Nawi

  4. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

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Irsalinda, N., Yanto, I.T.R., Chiroma, H., Herawan, T. (2017). A Framework of Clustering Based on Chicken Swarm Optimization. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_34

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  • DOI: https://doi.org/10.1007/978-3-319-51281-5_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51279-2

  • Online ISBN: 978-3-319-51281-5

  • eBook Packages: EngineeringEngineering (R0)

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