Density prediction of ternary mixtures of ethanol + water + ionic liquid using backpropagation artificial neural networks
| dc.contributor.author | Morales, Jorge | |
| dc.contributor.author | Moldes, Óscar A | |
| dc.contributor.author | Iglesias-Otero, Manuel A | |
| dc.contributor.author | Mejuto, Juan C | |
| dc.contributor.author | Astray, Gonzalo | |
| dc.contributor.author | Cid, Antonio | |
| dc.date | 2015-08 | |
| dc.date.accessioned | 2020-08-13T08:02:30Z | |
| dc.date.available | 2020-08-13T08:02:30Z | |
| dc.description | Capítulo del libro "Bidyut K. Paul Satya P. Moulik. (2105). Ionic Liquid‐Based Surfactant Science: Formulation, Characterization, and Applications. Capítulo 21" | es_ES |
| dc.description.abstract | New insights in the prediction of density in ternary mixtures of ethanol + water + ionic liquid using backpropagation artificial neural network (ANN) have been investigated by our research group. These predictions have been compared with the corresponding ones with another model, that is, multiple linear regression (MLR), and the advantages of neural modeling versus traditional modeling MLR have been shown. | es_ES |
| dc.identifier.doi | https://doi.org/10.1002/9781118854501.ch21 | |
| dc.identifier.isbn | 9781118834190 | |
| dc.identifier.uri | https://reunir.unir.net/handle/123456789/10403 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | Ionic Liquid-Based Surfactant Science: Formulation, Characterization, and Applications | es_ES |
| dc.relation.ispartofseries | ;pag. 447-458 | |
| dc.relation.uri | https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118854501.ch21 | es_ES |
| dc.rights | restrictedAccess | es_ES |
| dc.subject | Scopus | es_ES |
| dc.title | Density prediction of ternary mixtures of ethanol + water + ionic liquid using backpropagation artificial neural networks | es_ES |
| dc.type | bookPart | es_ES |
| opencost.publication.doi | https://doi.org/10.1002/9781118854501.ch21 | |
| reunir.tag | ~ARI | es_ES |
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