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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/96957
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dc.contributor.authorLi, X.-
dc.contributor.authorZecchin, A.-
dc.contributor.authorMaier, H.-
dc.date.issued2015-
dc.identifier.citationEnvironmental Modelling and Software, 2015; 71:78-96-
dc.identifier.issn1364-8152-
dc.identifier.issn1873-6726-
dc.identifier.urihttp://hdl.handle.net/2440/96957-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityXuyuan Li, Aaron C. Zecchin, Holger R. Maier-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2015 Elsevier Ltd. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.envsoft.2015.05.013-
dc.subjectArtificial neural networks; Data-driven models; Partial mutual information; Kernel density estimation; Kernel bandwidth; Boundary issues; Hydrology and water resources; Input variable selection-
dc.titleImproving partial mutual information-based input variable selection by consideration of boundary issues associated with bandwidth estimation-
dc.typeJournal article-
dc.identifier.doi10.1016/j.envsoft.2015.05.013-
pubs.publication-statusPublished-
dc.identifier.orcidZecchin, A. [0000-0001-8908-7023]-
dc.identifier.orcidMaier, H. [0000-0002-0277-6887]-
Appears in Collections:Aurora harvest 3
Civil and Environmental Engineering publications

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