Use of machine learning techniques to model wind damage to forests
Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...
A hyper-heuristic ensemble method for static job-shop scheduling.
Journal Article
Hart, E., & Sim, K. (2016)
A hyper-heuristic ensemble method for static job-shop scheduling. Evolutionary Computation, 24(4), 609-635. https://doi.org/10.1162/EVCO_a_00183
We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conq...
A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation
Journal Article
Segredo, E., Seguro, C., Coromoto, L., & Hart, E. (2014)
A fuzzy logic controller applied to a diversity-based multi-objective evolutionary algorithm for single-objective optimisation. Soft Computing, 19(10), 2927-2945. https://doi.org/10.1007/s00500-014-1454-y
In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The...
Techniques for Auditing the ICT Carbon Footprint of an Organisation
Journal Article
Mouchet, C., Urquhart, N., & Kemmer, R. (2014)
Techniques for Auditing the ICT Carbon Footprint of an Organisation. International Journal of Green Computing, 5(1), 44-61. https://doi.org/10.4018/ijgc.2014010104
This article has presents an extensive survey of the state of the art in Green IT/S. The findings of the survey suggest that there is scope for a reliable carbon footprint aud...