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Details of Grant 

EPSRC Reference: GR/R92844/01
Title: Establishing the Performance Envelope of Dynet: a new type of history dependent neural network model with potential for process modelling
Principal Investigator: withers, Professor P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Materials
Organisation: University of Manchester, The
Scheme: ROPA
Starts: 21 April 2003 Ends: 20 April 2005 Value (£): 76,761
EPSRC Research Topic Classifications:
Intelligent & Expert Systems Materials Processing
EPSRC Industrial Sector Classifications:
Manufacturing
Related Grants:
Panel History:  
Summary on Grant Application Form
As part of a project modelling microstructure development during four stand rolling with Alcan, neural network approaches are being assessed. While such models show promise, our work on very complex datasets has identified the need for a more strategic, examination of their capabilities. To this end a new type of neural network model - Dynet has been proposed, but it is yet undeveloped. This is a 2-year feasibility study using idealised data sets to understand better its performance, capabilities, strengths and weaknesses as well as to optimise their architechture before they can be considered for real problems.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Organisation Website: http://www.man.ac.uk