Outputs (126)

An examination of tuneable, random search landscapes (1999)
Presentation / Conference
Smith, R., & Smith, J. (1999, June). An examination of tuneable, random search landscapes. Paper presented at Foundations of Genetic Algorithms 5, Morgan Kaufmann, San Francisco, USA

Replacement strategies in steady state genetic algorithms: Static environments (1999)
Presentation / Conference
Smith, J., & Vavak, F. (1999, June). Replacement strategies in steady state genetic algorithms: Static environments. Paper presented at Foundations of Genetic Algorithms 5, Morgan Kaufmann, San Francisco, USA

Protein structure prediction with evolutionary algorithms (1999)
Presentation / Conference
Krasnogor, N., Hart, W., Smith, J., & Pelta, D. (1999, June). Protein structure prediction with evolutionary algorithms. Paper presented at Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), Morgan Kaufmann, San Francisco, USA

Replacement strategies in steady state genetic algorithms: Dynamic environments (1999)
Journal Article
Smith, J., & Vavak, F. (1999). Replacement strategies in steady state genetic algorithms: Dynamic environments. Journal of Computing and Information Technology, 7(1), 49-60

Self adaptation in evolutionary algorithms (1998)
Thesis
Smith, J. Self adaptation in evolutionary algorithms. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/1099661

Evolutionary Algorithms are search algorithms based on the Darwinian metaphor of “Natural Selection”. Typically these algorithms maintain a population of individual solutions, each of which has a fitness attached to it, which in some way reflects the... Read More about Self adaptation in evolutionary algorithms.

Microprocessor design verification by two-phase evolution of variable length tests (1997)
Presentation / Conference
Smith, J., Bartley, M., & Fogarty, T. (1997, June). Microprocessor design verification by two-phase evolution of variable length tests. Paper presented at Proceedings of the 1997 IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, USA

Genetic selection of features for clustering and classification (1997)
Presentation / Conference
Smith, J., Fogarty, T. C., & Johnson, I. R. (1997, June). Genetic selection of features for clustering and classification. Paper presented at Genetic Algorithms in Image Processing and Vision, IEE Colloquium on, Houston, USA

Operator and parameter adaptation in genetic algorithms (1997)
Journal Article
Smith, J., & Fogarty, T. (1997). Operator and parameter adaptation in genetic algorithms. Soft Computing, 1(2), 81-87. https://doi.org/10.1007/s005000050009

Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance and the Darwinian metaphor of “Natural Selection”. These algorithms maintain a finite memory of individual points on the search landscape known as the... Read More about Operator and parameter adaptation in genetic algorithms.

Self adaptation of mutation rates in a steady state genetic algorithm (1996)
Presentation / Conference
Smith, J., & Fogarty, T. (1996, June). Self adaptation of mutation rates in a steady state genetic algorithm. Paper presented at Proceedings of the 1996 IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, USA

Recombination strategy adaptation via evolution of gene linkage (1996)
Presentation / Conference
Smith, J., & Fogarty, T. (1996, June). Recombination strategy adaptation via evolution of gene linkage. Paper presented at Proceedings of the 1996 IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, USA