{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T16:31:27Z","timestamp":1756312287077,"version":"3.28.0"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,5]]},"DOI":"10.1109\/ssci50451.2021.9660040","type":"proceedings-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T21:09:51Z","timestamp":1643058591000},"page":"1-8","source":"Crossref","is-referenced-by-count":10,"title":["Multistream Graph Attention Networks for Wind Speed Forecasting"],"prefix":"10.1109","author":[{"given":"Dogan","family":"Aykas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siamak","family":"Mehrkanoon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219947"},{"key":"ref31","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016","journal-title":"ArXiv Preprint"},{"key":"ref30","article-title":"How powerful are graph neural networks?","author":"xu","year":"2018","journal-title":"ArXiv Preprint"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01230"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICISCE.2018.00058"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.08.036"},{"key":"ref11","article-title":"TENT: Ten-sorized encoder transformer for temperature forecasting","author":"bilgin","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2021.01.036"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI47803.2020.9308323"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10707-019-00355-0"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.14428\/esann\/2021.ES2021-25"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00078"},{"key":"ref17","article-title":"Deep multi-stations weather forecasting: explainable recurrent convolutional neural networks","author":"abdellaoui","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref18","first-page":"802","article-title":"Convolutional lstm network: A machine learning approach for precipitation nowcasting","author":"xingjian","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2015.07.104"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"16453","DOI":"10.1007\/s00500-020-04954-0","article-title":"Temporal convolutional neural (ten) network for an effective weather forecasting using time-series data from the local weather station","volume":"24","author":"hewage","year":"2020","journal-title":"Soft Computing"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/S0960-1481(98)00001-9"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/72.554195"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.05.009"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/qj.3410"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2011.05.033"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI50451.2021.9659860"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.120902"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/qj.49711247414"},{"key":"ref9","article-title":"Deep coastal sea elements forecasting using U-Net based models","author":"fern\u00e1ndez","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14956"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ISGT-Asia.2016.7796524"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-020-00898-1"},{"key":"ref21","article-title":"Graph attention networks","author":"velickovi?","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/eScience.2018.00130"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s13351-019-8162-6"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"7","DOI":"10.5120\/ijca2016910497","article-title":"Sequence to sequence weather forecasting with long short-term memory recurrent neural networks","volume":"143","author":"zaytar","year":"2016","journal-title":"International Journal of Computer Applications"}],"event":{"name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","start":{"date-parts":[[2021,12,5]]},"location":"Orlando, FL, USA","end":{"date-parts":[[2021,12,7]]}},"container-title":["2021 IEEE Symposium Series on Computational Intelligence (SSCI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9659537\/9659538\/09660040.pdf?arnumber=9660040","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:56:45Z","timestamp":1652201805000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9660040\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,5]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/ssci50451.2021.9660040","relation":{},"subject":[],"published":{"date-parts":[[2021,12,5]]}}}