Multivariate regression (MVR) and different artificial neural network (ANN) models developed for optical transparency of conductive polymer nanocomposite films. | 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/Duygu_Bayram_Kara>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Saziye_Ugur>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.1016%2Fj.eswa.2022.117937>
foaf:homepage	<https://doi.org/10.1016/j.eswa.2022.117937>
dc:identifier	DBLP journals/eswa/DemirbayKU22 (xsd:string)
dc:identifier	DOI doi.org%2F10.1016%2Fj.eswa.2022.117937 (xsd:string)
dcterms:issued	2022 (xsd:gYear)
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rdfs:label	Multivariate regression (MVR) and different artificial neural network (ANN) models developed for optical transparency of conductive polymer nanocomposite films. (xsd:string)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Saziye_Ugur>
swrc:pages	117937 (xsd:string)
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dc:title	Multivariate regression (MVR) and different artificial neural network (ANN) models developed for optical transparency of conductive polymer nanocomposite films. (xsd:string)
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