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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

A P System for K-Medoids-Based Clustering

Author 1: Ping Guo Author 2: Jingya Xie
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 10 · Published 2018

DOI: https://doi.org/10.14569/IJACSA.2018.091005

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Abstract

The membrane computing model, also known as the P system, is a parallel and distributed computing system. K-medoids algorithm is one of the most famous algorithms in partition-based clustering algorithms, and has been widely used in data analysis and modern scientific research. Combining the P system with the k-medoids algorithm, the maximum parallelism calculated by the P system can effectively reduce the time complexity of the k-medoids clustering algorithm. Based on this, this paper proposes a cell-like P system with promoters and inhibitors based on k-medoids clustering, and then an instance is given to illustrate the practicability and effectiveness of the P system designed.

Keywords

P systems Clustering K-medoids-based clustering Membrane computing Parallel and distributed computing

How to Cite this Article

Guo, P., & Xie, J. (2018). A P System for K-Medoids-Based Clustering. International Journal of Advanced Computer Science and Applications, 9(10). https://doi.org/10.14569/IJACSA.2018.091005

Guo, Ping, and Jingya Xie. "A P System for K-Medoids-Based Clustering." International Journal of Advanced Computer Science and Applications, vol. 9, no. 10, 2018, https://doi.org/10.14569/IJACSA.2018.091005.

@article{Guo2018,
  title     = {A P System for K-Medoids-Based Clustering},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {10},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Ping Guo and Jingya Xie},
  doi       = {10.14569/IJACSA.2018.091005},
  url       = {https://doi.org/10.14569/IJACSA.2018.091005}
}

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