Automatic General of a Neural Network Architecture Using Evolutionary Computation

E. Vonk, L.C. Jain, L.P.J. Veelenturf, R. Johnson

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    Abstract

    This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture. It is a usual practice to use trial and error to find a suitable neural network architecture. This is not only time consuming but may not generate an optimal solution for a given problem. The use of evolutionary computation is a step towards automation in architecture generation. In this paper a brief introduction to the field is given as well as an implementation of automatic neural network generation using genetic programming
    Original languageUndefined
    Title of host publicationProceedings of the International Conference and Workshops ETD2000, Electronic Technology Directions to the year 2000
    Place of PublicationAdelaide, Ausralia
    PublisherIEEE
    Pages-
    Number of pages6
    ISBN (Print)9780818670855
    DOIs
    Publication statusPublished - 23 May 1995

    Publication series

    Name
    PublisherIEEE

    Keywords

    • METIS-113175
    • IR-16290

    Cite this

    Vonk, E., Jain, L. C., Veelenturf, L. P. J., & Johnson, R. (1995). Automatic General of a Neural Network Architecture Using Evolutionary Computation. In Proceedings of the International Conference and Workshops ETD2000, Electronic Technology Directions to the year 2000 (pp. -). Adelaide, Ausralia: IEEE. https://doi.org/10.1109/ETD.1995.403479