1 code implementation • 6 Dec 2022 • Richard J. Preen, Jim Smith
This paper discusses the development of an open source tool ACRO, (Automatic Checking of Research Outputs) to assist researchers and data governance teams by distinguishing between: research output that is safe to publish; output that requires further analysis; and output that cannot be published because it creates substantial risk of disclosing private data.
1 code implementation • 2 Dec 2022 • Jim Smith, Richard J. Preen, Andrew McCarthy, Alba Crespi-Boixader, James Liley, Simon Rogers
We present AI-SDC, an integrated suite of open source Python tools to facilitate Statistical Disclosure Control (SDC) of Machine Learning (ML) models trained on confidential data prior to public release.
no code implementations • 1 Mar 2021 • Richard J. Preen, Larry Bull
This article presents the first results from using a learning classifier system capable of performing adaptive computation with deep neural networks.
no code implementations • 23 Oct 2019 • Richard J. Preen, Stewart W. Wilson, Larry Bull
Learning classifier systems (LCS) are a framework for adaptively subdividing input spaces into an ensemble of simpler local approximations that together cover the domain.
no code implementations • 19 Dec 2018 • Richard J. Preen, Larry Bull, Andrew Adamatzky
The use of high-fidelity computational simulations promises to enable high-throughput hypothesis testing and optimisation of cancer therapies.
no code implementations • 25 Mar 2018 • Richard J. Preen, Jim Smith
This article presents a novel memetic algorithm which remains effective on larger initial hypergraphs.
no code implementations • 18 Oct 2016 • Richard J. Preen, Jiseon You, Larry Bull, Ioannis A. Ieropoulos
Microbial fuel cells (MFCs) perform wastewater treatment and electricity production through the conversion of organic matter using microorganisms.
no code implementations • 29 Jun 2015 • Richard J. Preen, Larry Bull
Design mining is the use of computational intelligence techniques to iteratively search and model the attribute space of physical objects evaluated directly through rapid prototyping to meet given objectives.
no code implementations • 2 Oct 2014 • Richard J. Preen, Larry Bull
The accuracy of various modelling algorithms used to estimate the fitness of evaluated individuals from the initial experiments is compared.
no code implementations • 13 Aug 2013 • Richard J. Preen, Larry Bull
The production of renewable and sustainable energy is one of the most important challenges currently facing mankind.
1 code implementation • 18 Apr 2012 • Richard J. Preen, Larry Bull
We have recently presented an initial study of evolutionary algorithms used to design vertical-axis wind turbines (VAWTs) wherein candidate prototypes are evaluated under approximated wind tunnel conditions after being physically instantiated by a 3D printer.
no code implementations • 18 Apr 2012 • Richard J. Preen, Larry Bull
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks.
no code implementations • 26 Jan 2012 • Richard J. Preen, Larry Bull
A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks.