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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/68668
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dc.contributor.authorLowndes, I.-
dc.contributor.authorDandy, G.-
dc.contributor.authorMarshall, T.-
dc.contributor.authorSchmidt, T.-
dc.contributor.authorN, G.-
dc.contributor.authorRaynor, G.-
dc.contributor.editorHardcastle, S.-
dc.contributor.editorMcKinnon, D.-
dc.date.issued2010-
dc.identifier.citationProceedings of the 13th US/North American Mine Ventilation Symposium, Sudbury, ON, Canada, June 2010 / Hardcastle & McKinnon (eds.), pp. 441-447-
dc.identifier.urihttp://hdl.handle.net/2440/68668-
dc.description.statementofresponsibilityI. S. Lowndes, G. C. Dandy, T. S. Marshall, T. B. Schmidt, N. G. Simpson, & G. P. Raynor-
dc.language.isoen-
dc.publisherSudbury, ONT: MIRARCO-
dc.rights© 2010, MIRARCO - Mining Innovation-
dc.titleOptimization of mine ventilation networks using genetic algorithms and artificial neural networks-
dc.typeConference paper-
dc.contributor.conferenceUS/North American Mine Ventilation Symposium (13th : 2010 : Sudbury, Ontario, Canada)-
dc.publisher.placeCanada-
pubs.publication-statusPublished-
dc.identifier.orcidDandy, G. [0000-0001-5846-7365]-
Appears in Collections:Aurora harvest 5
Civil and Environmental Engineering publications
Environment Institute publications

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