All Outputs (7)

A Comprehensive Study of the Efficiency of Type-Reduction Algorithms (2020)
Journal Article
Chen, C., Wu, D., Garibaldi, J. M., John, R. I., Twycross, J., & Mendel, J. M. (2021). A Comprehensive Study of the Efficiency of Type-Reduction Algorithms. IEEE Transactions on Fuzzy Systems, 29(6), 1556 -1566. https://doi.org/10.1109/tfuzz.2020.2981002

Improving the efficiency of type-reduction algorithms continues to attract research interest. Recently, there have been some new type-reduction approaches claiming that they are more efficient than the well-known algorithms such as the enhanced Karni... Read More about A Comprehensive Study of the Efficiency of Type-Reduction Algorithms.

Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17α−ethinylestradiol (2019)
Journal Article
Acheampong, E., Dryden, I. L., Wattis, J. A., Twycross, J., Scrimshaw, M. D., & Gomes, R. L. (2019). Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17α−ethinylestradiol. Computers and Chemical Engineering, 128, 477-487. https://doi.org/10.1016/j.compchemeng.2019.06.020

Mathematical modelling can play a key role in understanding as well as quantifying uncertainties surrounding the presence and fate of emerging pollutants in wastewater treatment processes (WWTPs). This paper presents for the first time a simplified e... Read More about Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17α−ethinylestradiol.

A new accuracy measure based on bounded relative error for time series forecasting (2017)
Journal Article
Chen, C., Twycross, J., & Garibaldi, J. M. (2017). A new accuracy measure based on bounded relative error for time series forecasting. PLoS ONE, 12(3), Article e0174202. https://doi.org/10.1371/journal.pone.0174202

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising c... Read More about A new accuracy measure based on bounded relative error for time series forecasting.

Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis (2016)
Journal Article
Bonthala, V. S., Mayes, S., Moreton, J., Blythe, M. J., Wright, V., May, S., Massawe, F., Mayes, S., & Twycross, J. (2016). Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis. PLoS ONE, 11(2), Article e0148771. https://doi.org/10.1371/journal.pone.0148771

Bambara groundnut (Vigna subterranea (L.) Verdc.) is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth... Read More about Identification of gene modules associated with low temperatures response in Bambara groundnut by network-based analysis.

Stochastic and deterministic multiscale models for systems biology: An auxin-transport case study (2010)
Journal Article
Twycross, J., Band, L. R., Bennett, M. J., King, J. R., & Krasnogor, N. (2010). Stochastic and deterministic multiscale models for systems biology: An auxin-transport case study. BMC Systems Biology, 4, https://doi.org/10.1186/1752-0509-4-34

Background: Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modellin... Read More about Stochastic and deterministic multiscale models for systems biology: An auxin-transport case study.

Detecting anomalous process behaviour using second generation Artificial Immune Systems (2010)
Journal Article
Twycross, J., Aickelin, U., & Whitbrook, A. (2010). Detecting anomalous process behaviour using second generation Artificial Immune Systems. International Journal of Unconventional Computing, 6(3-4),

Artificial Immune Systems have been successfully applied to a number of problem domains including fault tolerance and data mining, but have been shown to scale poorly when applied to computer intrusion detection despite the fact that the biological i... Read More about Detecting anomalous process behaviour using second generation Artificial Immune Systems.

Information fusion in the immune system
Journal Article
Twycross, J., & Aickelin, U. Information fusion in the immune system. Information Fusion, 11(1), https://doi.org/10.1016/j.inffus.2009.04.008

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial immune systems (AISs) are a biologically-inspired approach which take inspiration from the biological... Read More about Information fusion in the immune system.