Renewable Energy Optimization, Planning and Control: Proceedings of ICRTE 2022
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
Springer Nature Singapore
2023
Singapore Springer |
| Ausgabe: | 1st ed. 2023 |
| Schriftenreihe: | Studies in Infrastructure and Control
|
| Schlagworte: | |
| Online-Zugang: | DE-522 DE-634 DE-1043 DE-1102 DE-1046 DE-1028 DE-Aug4 DE-1050 DE-573 DE-M347 DE-92 DE-898 DE-859 DE-861 DE-863 DE-862 DE-523 DE-703 DE-706 Volltext |
| Beschreibung: | 1 Online-Ressource (XVI, 466 p. 235 illus., 170 illus. in color) |
| ISBN: | 9789811989636 |
| ISSN: | 2730-6461 |
| DOI: | 10.1007/978-981-19-8963-6 |
Internformat
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Datensatz im Suchindex
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| discipline | Informatik Elektrotechnik |
| discipline_str_mv | Informatik Elektrotechnik |
| doi_str_mv | 10.1007/978-981-19-8963-6 |
| edition | 1st ed. 2023 |
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| id | DE-604.BV048886129 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T21:47:15Z |
| indexdate | 2024-08-05T08:38:47Z |
| institution | BVB |
| isbn | 9789811989636 |
| issn | 2730-6461 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034150773 |
| oclc_num | 1376406733 |
| open_access_boolean | |
| owner | DE-1028 DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-523 DE-859 DE-863 DE-BY-FWS DE-1050 DE-862 DE-BY-FWS DE-92 DE-522 DE-573 DE-M347 DE-703 DE-1102 DE-706 DE-634 |
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| physical | 1 Online-Ressource (XVI, 466 p. 235 illus., 170 illus. in color) |
| psigel | ZDB-2-ENE ZDB-2-ENE_2023 ZDB-2-ENE FHM_PDA_ENE_Kauf |
| publishDate | 2023 |
| publishDateSearch | 2023 |
| publishDateSort | 2023 |
| publisher | Springer Nature Singapore Springer |
| record_format | marc |
| series2 | Studies in Infrastructure and Control |
| spellingShingle | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 Computational Intelligence Machine Learning Control Structures and Microprogramming Renewable Energy Computational intelligence Machine learning Microprogramming Renewable energy sources |
| title | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 |
| title_auth | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 |
| title_exact_search | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 |
| title_exact_search_txtP | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 |
| title_full | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 edited by Anita Khosla, Mohan Kolhe |
| title_fullStr | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 edited by Anita Khosla, Mohan Kolhe |
| title_full_unstemmed | Renewable Energy Optimization, Planning and Control Proceedings of ICRTE 2022 edited by Anita Khosla, Mohan Kolhe |
| title_short | Renewable Energy Optimization, Planning and Control |
| title_sort | renewable energy optimization planning and control proceedings of icrte 2022 |
| title_sub | Proceedings of ICRTE 2022 |
| topic | Computational Intelligence Machine Learning Control Structures and Microprogramming Renewable Energy Computational intelligence Machine learning Microprogramming Renewable energy sources |
| topic_facet | Computational Intelligence Machine Learning Control Structures and Microprogramming Renewable Energy Computational intelligence Machine learning Microprogramming Renewable energy sources |
| url | https://doi.org/10.1007/978-981-19-8963-6 |
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