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Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique

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Abstract

The purpose of this study is the application of meta-heuristic algorithms and fuzzy logic in the optimization and clustering to predict the sawability of dimension stone. Survey and classification of dimension stones based on their physical and mechanical properties can be so impressive in the optimization of machine applications that are in this industry such as circular diamond saw block cutting machine. In this paper, physical and mechanical properties were obtained from laboratory testing on dimension stone block samples collected from 12 quarries located in Iran and their results were optimized and classified by one of the strongest meta-heuristic algorithms and fuzzy clustering technique. The clustering of dimension stone was determined by Lloyd’s algorithm (k-means clustering) based on imperialist competitive algorithm and fuzzy C-mean by MATLAB software. The hourly production rate of each studied dimension stones was considered as a criterion to evaluate the clustering efficacy. The results of this study showed that the Imperialist Competitive algorithm and fuzzy C-mean are very suitable for clustering with respect to the physical and mechanical properties of the dimension stone, and the results obtained showed the superiority of the ICA.

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Acknowledgments

We would like to express our deepest thanks to Professor Mahdi Ghaem for his excellent advice. We are also grateful to anonymous reviewers for their advices and contributions to this paper.

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Authors and Affiliations

  1. Department of Mining and Metallurgical Engineering, Urmia University of Technology, Urmia, Iran

    Reza Mikaeil

  2. Young Researchers and Elite Club, Rasht Branch, Islamic Azad University, Rasht, Iran

    Sina Shaffiee Haghshenas

  3. Department of Civil Engineering, Islamic Azad University, Astara Branch, Astara, Iran

    Sami Shaffiee Haghshenas

  4. Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran

    Mohammad Ataei

Authors
  1. Reza Mikaeil
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  2. Sina Shaffiee Haghshenas
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  3. Sami Shaffiee Haghshenas
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  4. Mohammad Ataei
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Correspondence to Sina Shaffiee Haghshenas.

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Mikaeil, R., Haghshenas, S.S., Haghshenas, S.S. et al. Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique. Neural Comput & Applic 29, 283–292 (2018). https://doi.org/10.1007/s00521-016-2557-4

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  • DOI: https://doi.org/10.1007/s00521-016-2557-4

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