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Application of artificial neural networks to predictions of aggregate quality parameters
Luleå tekniska universitet.
1999 (English)In: International Journal of Rock Mechanics And Mining Sciences, ISSN 1365-1609, E-ISSN 1873-4545, Vol. 36, no 4, p. 551-561Article in journal (Refereed) Published
Abstract [en]

A back propagation neural network was applied for predictions of aggregate quality parameters, impact value (SPR), abrasion value I (SL) and abrasion value II (KK) in a data set including 56 rock samples from south-west Sweden. The Leaving-One-Out technique was used to determine error rates for the difference between values predicted by the neural network and observed values. The predictive power of the neural network was compared with statistical regression models established previously. The optimal configuration of the neural networks as well as the optimal number of training epochs were established from experiments

Place, publisher, year, edition, pages
1999. Vol. 36, no 4, p. 551-561
National Category
Other Civil Engineering
Research subject
Mining and Rock Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-12614DOI: 10.1016/S0148-9062(99)00028-5ISI: 000081713500010Local ID: bc51ceb0-fc0b-11dc-a946-000ea68e967bOAI: oai:DiVA.org:ltu-12614DiVA, id: diva2:985565
Note
Godkänd; 1999; 20080327 (cira)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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