Zhao, J., Knight, B., Nissan, E., Petridis, M. and Soper, A.J. ORCID: https://orcid.org/0000-0002-0901-9803 (1998) The FUELGEN alternative: an evolutionary approach. The architecture. New Review of Applied Expert Systems, 4. pp. 177-183. ISSN 1361-0244

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Abstract

This paper introduces a few architectural concepts from FUELGEN, that generates a "cloud" of reload patterns, like the generator in the FUELCON expert system, but unlike that generator, is based on a genetic algorithm. There are indications FUELGEN may outperform FUELCON and other tools as reported in the literature, in well-researched case studies, but careful comparisons have to be carried out. This paper complements the information in two other recent papers on FUELGEN. Moreover, a sequel project is outlined.

Item Type:	Article
Additional Information:	[1] The New Review of Applied Expert Systems was subsequently known as the New Review of Applied Expert Systems and Emerging Technologies.
Uncontrolled Keywords:	computer architecture, genetic algorithms, trees (mathematics), FUELGEN expert system, expert systems
Subjects:	Q Science > QC Physics
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Computer & Computational Science Research Group School of Computing & Mathematical Sciences > Department of Computer Science School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Related URLs:	Publisher
Last Modified:	14 Oct 2016 08:59
URI:	http://gala.gre.ac.uk/id/eprint/97

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