Outputs (126)

A comparison of two memetic algorithms for software class modelling (2013)
Presentation / Conference
Smith, J., & Simons, C. (2013, July). A comparison of two memetic algorithms for software class modelling. Paper presented at Genetic and Evolutionary Computation Conference 2013 (GECCO 2013), Amsterdam, Netherlands

Recent research has demonstrated that the problem of class modelling within early cycle object orientated software engineering can be successfully tackled by posing it as a search problem to be tackled with meta-heuristics. This “Search Based Softwa... Read More about A comparison of two memetic algorithms for software class modelling.

A comparison of evolutionary algorithms and ant colony optimization for interactive software design (2012)
Presentation / Conference
Simons, C., & Smith, J. (2012, September). A comparison of evolutionary algorithms and ant colony optimization for interactive software design. Paper presented at 4th Symposium on Search Based-Software Engineering, Riva del Garda, Trento, Italy

Self-adaptative and coevolving memetic algorithms (2012)
Book Chapter
Smith, J. (2012). Self-adaptative and coevolving memetic algorithms. In F. Neri, C. Cotta, & P. Moscato (Eds.), Handbook of Memetic Algorithms (167-188). Springer

Making early predictions of the accuracy of machine learning classifiers (2012)
Book Chapter
Smith, J., Tahir, M., Sannen, D., & Van Brussel, H. (2012). Making early predictions of the accuracy of machine learning classifiers. In M. Sayed-Mouchaweh, & E. Lughofer (Eds.), Learning in Non-Stationary Environments (125-151). Springer

Scaling up a hybrid genetic linear programming algorithm for statistical disclosure control (2011)
Presentation / Conference
Serpell, M., Smith, J., Clark, A., & Staggemeier, A. T. (2011, July). Scaling up a hybrid genetic linear programming algorithm for statistical disclosure control. Paper presented at 13th annual conference on Genetic and evolutionary computation, Dublin, Ireland

Aspect oriented software fault tolerance and analytically redundant design framework (2010)
Conference Proceeding
Hameed, K., Williams, R., & Smith, J. (2010). Aspect oriented software fault tolerance and analytically redundant design framework. In 2010 International Conference on Dependable Systems and Networks Workshops (DSN-W) (38-44). https://doi.org/10.1109/DSNW.2010.5542623

Diversity or redundancy based software fault tolerance does not come for free; rather it introduces additional complexity to the core functionality in the form of redundancy development, management and controlled execution. This results in tangling o... Read More about Aspect oriented software fault tolerance and analytically redundant design framework.

Self-adaptation of mutation operator and probability for permutation representations in genetic algorithms (2010)
Journal Article
Serpell, M., & Smith, J. (2010). Self-adaptation of mutation operator and probability for permutation representations in genetic algorithms. Evolutionary Computation, 18(3), 491-514. https://doi.org/10.1162/EVCO_a_00006

The choice of mutation rate is a vital factor in the success of any genetic algorithm (GA), and for permutation representations this is compounded by the availability of several alternative mutation operators. It is now well understood that there is... Read More about Self-adaptation of mutation operator and probability for permutation representations in genetic algorithms.

Teaching problem solving and AI with PacMan (2010)
Presentation / Conference
Smith, J., & Cayzer, S. (2010, August). Teaching problem solving and AI with PacMan. Paper presented at Proceedings of the 11th Annual Conference on the Teaching of Computing, Higher Education Academy Information and Computer Sciences Subject Centre (HEA-ICS), Durham University, UK

Impact of object extraction methods on classification performance in surface inspection systems (2010)
Journal Article
Raiser, S., Lughofer, E., Eitzinger, C., & Smith, J. (2010). Impact of object extraction methods on classification performance in surface inspection systems. Machine Vision and Applications, 21(5), 627-641. https://doi.org/10.1007/s00138-009-0205-z

In surface inspection applications, the main goal is to detect all areas which might contain defects or unacceptable imperfections, and to classify either every single 'suspicious' region or the investigated part as a whole. After an image is acquire... Read More about Impact of object extraction methods on classification performance in surface inspection systems.

Assessment of the influence of adaptive components in trainable surface inspection systems (2010)
Journal Article
Van Brussel, H., Eitzinger, C., Heidl, W., Lughofer, E., Raiser, S., Smith, J., …Sannen, D. (2010). Assessment of the influence of adaptive components in trainable surface inspection systems. Machine Vision and Applications, 21(5), 613-626. https://doi.org/10.1007/s00138-009-0211-1

In this paper, we present a framework for the classification of images in surface inspection tasks and address several key aspects of the processing chain from the original image to the final classification result. A major contribution of this paper... Read More about Assessment of the influence of adaptive components in trainable surface inspection systems.