Deep Learning-Based Auto-LSTM Approach for Renewable Energy Forecasting: A Hybrid Network Model.
Saved in:
| Title: | Deep Learning-Based Auto-LSTM Approach for Renewable Energy Forecasting: A Hybrid Network Model. |
|---|---|
| Authors: | Venkatraman, Deenadayalan1 deenadayalan.venkataraman@wipro.com, Pitchaipillai, Vaishnavi1 |
| Source: | Traitement du Signal. Feb2024, Vol. 41 Issue 1, p525-530. 6p. |
| Database: | Business Source Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: bsu DbLabel: Business Source Ultimate An: 175839383 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Deep Learning-Based Auto-LSTM Approach for Renewable Energy Forecasting: A Hybrid Network Model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Venkatraman%2C+Deenadayalan%22">Venkatraman, Deenadayalan</searchLink><relatesTo>1</relatesTo><i> deenadayalan.venkataraman@wipro.com</i><br /><searchLink fieldCode="AR" term="%22Pitchaipillai%2C+Vaishnavi%22">Pitchaipillai, Vaishnavi</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Traitement+du+Signal%22">Traitement du Signal</searchLink>. Feb2024, Vol. 41 Issue 1, p525-530. 6p. |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=175839383 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.18280/ts.410148 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 525 Titles: – TitleFull: Deep Learning-Based Auto-LSTM Approach for Renewable Energy Forecasting: A Hybrid Network Model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Venkatraman, Deenadayalan – PersonEntity: Name: NameFull: Pitchaipillai, Vaishnavi IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 07650019 Numbering: – Type: volume Value: 41 – Type: issue Value: 1 Titles: – TitleFull: Traitement du Signal Type: main |
| ResultId | 1 |