Global optimization using meta-controlled Boltzmann machine

Shamshul Bahar Yaakob, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this study, a new artificial neuron network model called the meta-controlled Boltzmann machine is introduced. The meta-controlled Boltzmann machine model includes the McCulloch-Pitts model, the Hopfield network, and also the Boltzmann machine. The proposed method are applied both diffusion processes and simulated annealing. The convergence proof of the proposed method is shows in this paper. Meta-controlled Boltzmann machine show an ability to solve combinatorial optimization problems better than either Hopfield networks or Boltzmann machines.

    Original languageEnglish
    Title of host publicationProceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
    Pages39-42
    Number of pages4
    DOIs
    Publication statusPublished - 2010
    Event4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 - Shenzhen
    Duration: 2010 Dec 132010 Dec 15

    Other

    Other4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
    CityShenzhen
    Period10/12/1310/12/15

    Keywords

    • Boltzmann machine
    • Hopfield networks
    • Meta-controlled Boltzmann machine
    • Neural network
    • Simulated annealing

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Theoretical Computer Science

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  • Cite this

    Yaakob, S. B., & Watada, J. (2010). Global optimization using meta-controlled Boltzmann machine. In Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010 (pp. 39-42). [5715365] https://doi.org/10.1109/ICGEC.2010.18