Realization of Low-Code Algorithm for Steel Energy Consumption Prediction
The steel industry is one of the world's highest energy consumption. It is important to improve its energy efficiency. Energy consumption prediction can help steel industry better plan and manage energy use. Based on a low-code development platform, multiple prediction algorithm models are used...
Gespeichert in:
| Veröffentlicht in: | IEEE International Conference on Computer Communication and the Internet (Online) S. 206 - 210 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
14.06.2024
|
| Schlagworte: | |
| ISSN: | 2833-2350 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | The steel industry is one of the world's highest energy consumption. It is important to improve its energy efficiency. Energy consumption prediction can help steel industry better plan and manage energy use. Based on a low-code development platform, multiple prediction algorithm models are used to predict the energy consumption. A low-code algorithmic platform support is provided for the steel industry to achieve energy saving and efficiency improvement. |
|---|---|
| AbstractList | The steel industry is one of the world's highest energy consumption. It is important to improve its energy efficiency. Energy consumption prediction can help steel industry better plan and manage energy use. Based on a low-code development platform, multiple prediction algorithm models are used to predict the energy consumption. A low-code algorithmic platform support is provided for the steel industry to achieve energy saving and efficiency improvement. |
| Author | Bian, Yunqi Cai, Hongxia Ji, Wanzhou |
| Author_xml | – sequence: 1 givenname: Wanzhou surname: Ji fullname: Ji, Wanzhou email: 15161971811@shu.edu.cn organization: School of Mechatronic Engineering and Automation Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China – sequence: 2 givenname: Yunqi surname: Bian fullname: Bian, Yunqi email: bianyunqi@shu.edu.cn organization: School of Mechatronic Engineering and Automation Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China – sequence: 3 givenname: Hongxia surname: Cai fullname: Cai, Hongxia email: hxcai@staff.shu.edu.cn organization: School of Mechatronic Engineering and Automation Shanghai University,Shanghai Key Laboratory of Intelligent Manufacturing and Robotics,Shanghai,China |
| BookMark | eNo1j9tKxDAYhKMouK59Ay_yAq1_kiZNLpewuoWC4uF6Sbd_10jbLGlF1qe3nq5mGJjhm0tyNoQBCaEMMsbA3JTW2lJxJk3GgecZA1XkiusTkpjCaCFBSFao4pQsuBYi5XNyQZJxfAMAwRkrhFqQ8hFd5z_d5MNAQ0ur8JHa0CBddfsQ_fTa0zZE-jQhdnQ9YNwfqQ3D-N4ffioPERu_-7ZX5Lx13YjJny7Jy-362W7S6v6utKsq9TPNlDayybWEVvO6ljpXzqBwgMBrgbtGGQG1NjMgcqeN0XPmmG7rFkHqQqpGLMn1765HxO0h-t7F4_b_vfgCcWNQ7A |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/ICCCI62159.2024.10674628 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE/IET Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE/IET Electronic Library (IEL) (UW System Shared) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798350351767 |
| EISSN | 2833-2350 |
| EndPage | 210 |
| ExternalDocumentID | 10674628 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL 6IN AAWTH ABLEC ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK OCL RIE RIL |
| ID | FETCH-LOGICAL-i176t-d5d4850f82bb5846a9e3a0e02b3ecd6930b89003e2a8998ecda18fbfe058756d3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 0 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001332839400035&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 01:59:43 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i176t-d5d4850f82bb5846a9e3a0e02b3ecd6930b89003e2a8998ecda18fbfe058756d3 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_10674628 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-June-14 |
| PublicationDateYYYYMMDD | 2024-06-14 |
| PublicationDate_xml | – month: 06 year: 2024 text: 2024-June-14 day: 14 |
| PublicationDecade | 2020 |
| PublicationTitle | IEEE International Conference on Computer Communication and the Internet (Online) |
| PublicationTitleAbbrev | ICCCI |
| PublicationYear | 2024 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0003211736 |
| Score | 1.8732334 |
| Snippet | The steel industry is one of the world's highest energy consumption. It is important to improve its energy efficiency. Energy consumption prediction can help... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 206 |
| SubjectTerms | Computational modeling Deep Learning Energy conservation Energy consumption Energy Consumption Prediction Energy efficiency Low-Code Development Platform Prediction algorithms Predictive models Steel industry |
| Title | Realization of Low-Code Algorithm for Steel Energy Consumption Prediction |
| URI | https://ieeexplore.ieee.org/document/10674628 |
| WOSCitedRecordID | wos001332839400035&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ1LSwMxEICDFg-eVKz4JgevaXeT7CZ7lKXFQinFF72VZDOrhdqVutW_bybdVjx48BYCCWECmVe-GUJulIOMJ2XCtOEpk1kkmIkdMGESWxaZtmkoX_w8VKORnkyycQOrBxYGAMLnM-jgMOTyXVWsMFTWxXJnyFLukl2l1BrW2gZUhHdlFKYiaVNHszvI83yQep2GQAqXnc3yX41Ugh7pH_zzBIek_UPk0fFW1xyRHVgck8G9t_IajpJWJR1WXyyvHNDb-Uvlnf7XN-pNUvpQA8xpL0B-NA_IZXgn_IaYpcFhmzz1e4_5HWtaI7BZrNKaucRJnUSl5taiCWEyECaCiFsBhcP2hlZjjBK4QYfKz5lYl7aEKPEOSurECWktqgWcEiqVjlJdCp7YTIKQJnWlwjAHL6zLZHFG2iiH6fu6-sV0I4LzP-YvyD5KG79TxfKStOrlCq7IXvFZzz6W1-HOvgEgyZdf |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3NS8MwFMCDTkFPKk78Ngev2dp8tOlRyobDOoZO2W0kzasO5iqz03_fJOsmHjx4C-8QwgvkfeX3HkLXsYGEikIQqWhEeBIwokIDhCmhizyROvLti5-zuN-Xo1EyqGF1z8IAgP98Bi239LV8U-YLlypru3ZnjqXcRFuCcxouca11SoXZYCZ2xUhcd9Js99I07UXWqjkkhfLWaoNfo1S8Jenu_fMM-6j5w-ThwdraHKANmB2i3oP182qSEpcFzsovkpYG8M30pbRh_-sbtk4pfqwAprjjMT-ceujSvxR2Q1enccsmeup2huktqYcjkEkYRxUxwnApgkJSrZ0ToRJgKoCAaga5cQMOtXRZSqDKhVRWpkJZ6AICYUOUyLAj1JiVMzhGmMcyiGTBqNAJB8ZVZIrYJTpork3C8xPUdHoYvy_7X4xXKjj9Q36Fdm6H99k46_XvztCu07z7XBXyc9So5gu4QNv5ZzX5mF_6-_sGMoOapg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=IEEE+International+Conference+on+Computer+Communication+and+the+Internet+%28Online%29&rft.atitle=Realization+of+Low-Code+Algorithm+for+Steel+Energy+Consumption+Prediction&rft.au=Ji%2C+Wanzhou&rft.au=Bian%2C+Yunqi&rft.au=Cai%2C+Hongxia&rft.date=2024-06-14&rft.pub=IEEE&rft.eissn=2833-2350&rft.spage=206&rft.epage=210&rft_id=info:doi/10.1109%2FICCCI62159.2024.10674628&rft.externalDocID=10674628 |