All Outputs (4)

Applications of Evolutionary Computation (2017)
Conference Proceeding
(2017). Applications of Evolutionary Computation. In G. Squillero, & K. Sim (Eds.), Applications of Evolutionary Computation (Part II). https://doi.org/10.1007/978-3-319-55792-2

The two volumes LNCS 10199 and 10200 constitute the refereed conference proceedings of the 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, held in Amsterdam, The Netherlands, in April 2017, colocated wi... Read More about Applications of Evolutionary Computation.

Applications of Evolutionary Computation (2017)
Conference Proceeding
(2017). Applications of Evolutionary Computation. In G. Squillero, & K. Sim (Eds.), Applications of Evolutionary Computation (Part I). https://doi.org/10.1007/978-3-319-55849-3

The two volumes LNCS 10199 and 10200 constitute the refereed conference proceedings of the 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, held in Amsterdam, The Netherlands, in April 2017, collocated w... Read More about Applications of Evolutionary Computation.

A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector (2017)
Conference Proceeding
Hart, E., Sim, K., Gardiner, B., & Kamimura, K. (2017). A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference (1121-1128). https://doi.org/10.1145/3071178.3071217

Catastrophic damage to forests resulting from major storms has resulted in serious timber and financial losses within the sector across Europe in the recent past. Developing risk assessment methods is thus one of the keys to finding forest management... Read More about A hybrid method for feature construction and selection to improve wind-damage prediction in the forestry sector.

On Constructing Ensembles for Combinatorial Optimisation (2017)
Journal Article
Hart, E., & Sim, K. (2018). On Constructing Ensembles for Combinatorial Optimisation. Evolutionary Computation, 26(1), 67-87. https://doi.org/10.1162/evco_a_00203

Although the use of ensemble methods in machine-learning is ubiquitous due to their proven ability to outperform their constituent algorithms, ensembles of optimisation algorithms have received relatively little attention. Existing approaches lag beh... Read More about On Constructing Ensembles for Combinatorial Optimisation.