Machine learning approach to handle data-driven model for simulation and forecasting of the cone crusher output in the stone crushing plant. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Khaled_Ali_Abuhasel>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.1111%2Fcoin.12338>
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dc:identifier	DBLP journals/ci/Abuhasel21 (xsd:string)
dc:identifier	DOI doi.org%2F10.1111%2Fcoin.12338 (xsd:string)
dcterms:issued	2021 (xsd:gYear)
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rdfs:label	Machine learning approach to handle data-driven model for simulation and forecasting of the cone crusher output in the stone crushing plant. (xsd:string)
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swrc:pages	1098-1110 (xsd:string)
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rdfs:seeAlso	<https://doi.org/10.1111/coin.12338>
dc:title	Machine learning approach to handle data-driven model for simulation and forecasting of the cone crusher output in the stone crushing plant. (xsd:string)
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