| Download | - View accepted manuscript: Utilization of neural networks to expand databases (PDF, 226 KiB)
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| Author | Search for: Khogali, W. E. I.1; Search for: Zeghal, M.1 |
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| Affiliation | - National Research Council of Canada. NRC Institute for Research in Construction
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| Format | Text, Article |
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| Conference | CANCAM 2007, 3 June 2007, Toronto, Ontario |
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| Subject | Roads |
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| Abstract | This paper examines the potential use of the artificial neural networks (ANN) technique as a tool for expanding databases. The application presented in the paper targets databases that house mechanistic properties of aggregate materials, commonly used in road base and sub-base layers. The research involved the development and utilization of an ANN model to populate a resilient modulus database of granular materials from limited laboratory-generated data. The ANN model was used to test resilient moduli under a variety of test conditions, including aggregate density, stress and moisture content to assess the effect of input parameters on the resilient response (the output). |
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| Publication date | 2007-06-03 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NRC number | NRCC 49248
NRC-IRC-18352 |
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| NPARC number | 20377808 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | b8e00a7f-72d0-40d8-babe-23de005a6d3f |
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| Record created | 2012-07-24 |
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| Record modified | 2020-05-10 |
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