{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T16:17:18Z","timestamp":1781281038210,"version":"3.54.1"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000780","name":"BEGONIA Project through European Commission","doi-asserted-by":"publisher","award":["01133306"],"award-info":[{"award-number":["01133306"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"name":"FAST Community"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Smart Grid"],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1109\/tsg.2025.3570955","type":"journal-article","created":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T13:57:36Z","timestamp":1747663056000},"page":"3210-3225","source":"Crossref","is-referenced-by-count":12,"title":["Causality-Aware Multi-Graph Convolutional Networks With Critical Node Dynamics for Electric Vehicle Charging Station Load Forecasting"],"prefix":"10.1109","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3437-1120","authenticated-orcid":false,"given":"Yaohui","family":"Huang","sequence":"first","affiliation":[{"name":"School of Automation, Central South University, Changsha, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Senzhen","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Computer Engineering, Jimei University, Xiamen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhijin","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Engineering, Jimei University, Xiamen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5133-6688","authenticated-orcid":false,"given":"Xiufeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Technology, Management and Economics, Technical University of Denmark, Lyngby, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5627-2898","authenticated-orcid":false,"given":"Chendan","family":"Li","sequence":"additional","affiliation":[{"name":"DITEN, University of Genoa, Genova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Computer Engineering, Jimei University, Xiamen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/s41560-022-01105-7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2022.3191530"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-51554-9"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3048728"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2022.3186870"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2023.129213"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TTE.2023.3299417"},{"key":"ref8","first-page":"17804","article-title":"Adaptive graph convolutional recurrent network for traffic forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Bai"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2024.3368419"},{"key":"ref10","first-page":"1","article-title":"FourierGNN: Rethinking multivariate time series forecasting from a pure graph perspective","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Yi"},{"issue":"99","key":"ref11","first-page":"1","article-title":"Joint causal inference from multiple contexts","volume":"21","author":"Mooij","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3501714.3501736"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1093\/pan\/mps040"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/OJVT.2024.3457499"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2023.3344544"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2024.108789"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref18","first-page":"1","article-title":"Crossformer: Transformer Utilizing cross-dimension dependency for multivariate time series forecasting","volume-title":"Proc. 11th Int. Conf. Learn. Represent.","author":"Zhang"},{"key":"ref19","first-page":"1","article-title":"A time series is worth 64 words: Long-term forecasting with transformers","volume-title":"Proc. 11th Int. Conf. Learn. Represent.","author":"Nie"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3276947"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3168577"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2990397"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2023.127911"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3268199"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/264"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2023.3321116"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2024.3401850"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2023.3311795"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2023.3296870"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2024.120868"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28707"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.2307\/1912791.1969"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10448031"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2023.121783"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1038\/s41893-022-01058-5"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117921"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.105893"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220104"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-024-02942-9"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2024.3449339"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1406.1078"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25854"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-040120-010930"}],"container-title":["IEEE Transactions on Smart Grid"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5165411\/11048363\/11007094.pdf?arnumber=11007094","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T17:30:41Z","timestamp":1757698241000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11007094\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":44,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tsg.2025.3570955","relation":{},"ISSN":["1949-3053","1949-3061"],"issn-type":[{"value":"1949-3053","type":"print"},{"value":"1949-3061","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7]]}}}