Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield.
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| Title: | Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield. |
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| Authors: | Keane, Michael1 (AUTHOR) m.keane@unsw.edu.au, Neal, Timothy1 (AUTHOR) timothy.neal@unsw.edu.au |
| Source: | Econometrics Journal. Sep2020, Vol. 23 Issue 3, pS59-S80. 22p. |
| Database: | Business Source Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: bsu DbLabel: Business Source Ultimate An: 146514877 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Keane%2C+Michael%22">Keane, Michael</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> m.keane@unsw.edu.au</i><br /><searchLink fieldCode="AR" term="%22Neal%2C+Timothy%22">Neal, Timothy</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> timothy.neal@unsw.edu.au</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Econometrics+Journal%22">Econometrics Journal</searchLink>. Sep2020, Vol. 23 Issue 3, pS59-S80. 22p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=146514877 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/ectj/utaa012 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: S59 Titles: – TitleFull: Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Keane, Michael – PersonEntity: Name: NameFull: Neal, Timothy IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2020 Type: published Y: 2020 Identifiers: – Type: issn-print Value: 13684221 Numbering: – Type: volume Value: 23 – Type: issue Value: 3 Titles: – TitleFull: Econometrics Journal Type: main |
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