{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T05:49:11Z","timestamp":1783144151199,"version":"3.54.6"},"reference-count":26,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100016901","name":"Posts and Telecommunications Institute of Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100016901","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3570595","type":"journal-article","created":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T17:33:41Z","timestamp":1747330421000},"page":"88093-88104","source":"Crossref","is-referenced-by-count":6,"title":["Leveraging Edge Intelligence for Solar Energy Management in Smart Grids"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8486-2940","authenticated-orcid":false,"given":"Trong-Minh","family":"Hoang","sequence":"first","affiliation":[{"name":"Telecommunication Faculty, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tuan-Anh","family":"Pham","sequence":"additional","affiliation":[{"name":"Department of EdgeAI, AI Center, FPT Software, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4633-5242","authenticated-orcid":false,"given":"van-Nhan","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Information Technology Faculty, Dai Nam University, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duc-Thang","family":"Doan","sequence":"additional","affiliation":[{"name":"Telecommunication Faculty, Posts and Telecommunications Institute of Technology, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1565-4376","authenticated-orcid":false,"given":"Nhu-Ngoc","family":"Dao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Sejong University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICAAIC60222.2024.10575346"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-99-8886-0_8"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.125217"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/su16145940"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/en17133073"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.108502"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1002\/9781119812524.ch13"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/en17163965"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3390\/su16146102"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3390\/en17071781"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2024.119943"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2024.02.004"},{"key":"ref13","first-page":"154078","article-title":"A hybrid deep learning model for traffic flow prediction based on tcn and gru","volume":"9","author":"Hao","year":"2021","journal-title":"IEEE Access"},{"key":"ref14","first-page":"1096","article-title":"Multi-step wind speed prediction based on a hybrid tcn-gru model","volume-title":"Proc. IEEE Sustain. Power Energy Conf. (iSPEC)","author":"Li"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/su15031973"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref17","article-title":"TimesNet: Temporal 2D-variation modeling for general time series analysis","author":"Wu","year":"2022","journal-title":"arXiv:2210.02186"},{"key":"ref18","article-title":"Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting","author":"Wu","year":"2021","journal-title":"arXiv:2106.13008"},{"key":"ref19","first-page":"9881","article-title":"Non-stationary transformers: Exploring the stationarity in time series forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liu"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124286"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-024-09558-5"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/su16125240"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2024.122971"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/en17174360"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2016.02.001"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/11005531.pdf?arnumber=11005531","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T04:43:02Z","timestamp":1748061782000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11005531\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3570595","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}