Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP0208976
Funding Status
Closed
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Funded Activity Summary
Realising the promise of neural networks for practical optimisation: improving their efficiency and effectivess through chaotic dynamics and hardware implementation. Combinatorial optimisation problems such as transportation routing and assembly-line scheduling are critical to the efficiency of many industries, but their combinatorial explosion makes rapid solution difficult. Neural networks (NNs) hold much potential for rapid solution though hardware implementation, but we need to improve the quality of their solutions before developing hardware. We have previously shown that the rich dynamics of chaos can improve the efficiency and effectiveness of NNs. We aim to develop new chaotic NN models, rigorously evaluate them on industrially significant problems such as those arising in manufacturing, logistics and telecommunications, and demonstrate their speed through hardware acceleration.Funded Activity Details
Start Date: 2002
End Date: 12-2005
Funding Scheme: Discovery Projects
Funding Amount: $234,967.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Dynamical Systems | Neural Networks, Genetic Alogrithms And Fuzzy Logic | Optimisation | Artificial Intelligence and Image Processing
ANZSRC Socio-Economic Objective (SEO)
Computer software and services not elsewhere classified | Integrated circuits and devices | Mathematical sciences |
