Representation in the (Artificial) Immune System
Journal Article
McEwan, C., & Hart, E. (2009)
Representation in the (Artificial) Immune System. Journal of Mathematical Modelling and Algorithms, 8, 125-149. https://doi.org/10.1007/s10852-009-9104-6
Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausibl...
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...
Structure versus function: a topological perspective on immune networks
Journal Article
Hart, E., Bersini, H., & Santos, F. (2009)
Structure versus function: a topological perspective on immune networks. Natural Computing, https://doi.org/10.1007/s11047-009-9138-8
Many recent advances have been made in understanding the functional implications of the global topological properties of biological networks through the application of complex...
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...
Application areas of AIS: The past, the present and the future
Journal Article
Hart, E., & Timmis, J. (2008)
Application areas of AIS: The past, the present and the future. Applied Soft Computing, 8(1), 191-201. doi:10.1016/j.asoc.2006.12.004
After a decade of research into the area of artificial immune systems, it is worthwhile to take a step back and reflect on the contributions that the
paradigm has brought to t...
On artificial immune systems and swarm intelligence
Journal Article
Timmis, J., Andrews, P., & Hart, E. (2010)
On artificial immune systems and swarm intelligence. Swarm Intelligence, 4(4), 247-273. https://doi.org/10.1007/s11721-010-0045-5
This position paper explores the nature and role of two bio-inspired paradigms, namely Artificial Immune Systems (AIS) and Swarm Intelligence (SI). We argue that there are man...
A Lifelong Learning Hyper-heuristic Method for Bin Packing.
Journal Article
Hart, E., Sim, K., & Paechter, B. (2015)
A Lifelong Learning Hyper-heuristic Method for Bin Packing. Evolutionary Computation, 23(1), 37-67. https://doi.org/10.1162/EVCO_a_00121
We describe a novel Hyper-heuristic system which continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics ...