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Alternative cross-over strategies and selection techniques for grammatical evolution optimized neural networks

Published:08 July 2006Publication History

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References

  1. Motsinger A. A., Dudek S. M., Hahn L. W., and Ritchie M. D. Comparison of Neural Network Optimization Approaches for Studies of Human Genetics. Lecture Notes in Computer Science, 3907: 103--114. 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Moore J., Hahn L., Ritchie M., Thornton T., White B. Application of genetic algorithms to the discovery of complex models for simulation studies in human genetics. Langdon, W. B., Cantú-Paz, E., Mathias, K., Roy, R., Davis, D., Poli, R., Balakrishnan, K., Honavar, V., Rudolph, G., Wegener, J., Bull, L., Potter, M. A., Schultz, A. C., Miller, J. F., Burke, E., and Jonoska, N. Proceedings of the Genetic and Evolutionary Algorithm Conference. 1150--1155. 2002. San Francisco, Morgan Kaufman Publishers. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Alternative cross-over strategies and selection techniques for grammatical evolution optimized neural networks

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        cover image ACM Conferences
        GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation
        July 2006
        2004 pages
        ISBN:1595931864
        DOI:10.1145/1143997

        Copyright © 2006 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 8 July 2006

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        Acceptance Rates

        GECCO '06 Paper Acceptance Rate205of446submissions,46%Overall Acceptance Rate1,669of4,410submissions,38%

        Upcoming Conference

        GECCO '24
        Genetic and Evolutionary Computation Conference
        July 14 - 18, 2024
        Melbourne , VIC , Australia

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