{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T05:30:04Z","timestamp":1782970204170,"version":"3.54.5"},"reference-count":36,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72171068"],"award-info":[{"award-number":["72171068"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71771073"],"award-info":[{"award-number":["71771073"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Anhui Provincial Natural Science Foundation, China for Distinguished Young Scholars","award":["2108085J36"],"award-info":[{"award-number":["2108085J36"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Inf."],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1109\/tii.2022.3228383","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:42:06Z","timestamp":1670874126000},"page":"9447-9456","source":"Crossref","is-referenced-by-count":28,"title":["Day-Ahead Peak Load Probability Density Forecasting Based on QRLSTM-DF Considering Exogenous Factors"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5059-5151","authenticated-orcid":false,"given":"Yaoyao","family":"He","sequence":"first","affiliation":[{"name":"School of Management, Hefei University of Technology, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2683-2051","authenticated-orcid":false,"given":"Chaojin","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingling","family":"Xiao","sequence":"additional","affiliation":[{"name":"General Management Department, Conch Venture Holdings Limited, Wuhu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2019.2942024"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2825441"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114844"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106431"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3130237"},{"key":"ref14","first-page":"62","article-title":"Day-ahead base, intermediate, and peak load forecasting using K-means and artificial neural networks","volume":"9","author":"velasco","year":"2018","journal-title":"Int J Adv Comput Sci Appl"},{"key":"ref36","article-title":"Electrician mathematical contest in modeling","year":"2016"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115591"},{"key":"ref30","first-page":"66","article-title":"Feature decoupling peak-load forecasting model considering meteorological cumulative effect","volume":"46","author":"chuan","year":"2022","journal-title":"Automation of Electronic Power Systems"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"42","DOI":"10.4018\/IJSSCI.2020100103","article-title":"Information processing systems in UAV based on Bayesian filtering in conditions of uncertainty","volume":"12","author":"rinat","year":"2020","journal-title":"Int J Softw Sci Comput Intell"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2014.2370936"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2017.03.034"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.120069"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2019.2939988"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2930064"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2022.107860"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CAC.2017.8242744"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2002.800992"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2895604"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2021.127737"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3067043"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2018.10.078"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1002\/1099-131X(200007)19:4<299::AID-FOR775>3.0.CO;2-V"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICEICE.2011.5777343"},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1016\/j.energy.2021.120109","article-title":"Prediction of solar energy guided by Pearson correlation using machine learning","volume":"224","author":"jebli","year":"2021","journal-title":"Energy"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2995766"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.01.022"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2019.05.063"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.joule.2020.08.017"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3190034"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.4018\/IJSWIS.307908"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJSSCI.2020100101","article-title":"The optimal path finding algorithm based on reinforcement learning","volume":"12","author":"ganesh","year":"2020","journal-title":"Int J Softw Sci Comput Intell"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2946292"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.122366"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2017.08.135"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyr.2019.08.086"}],"container-title":["IEEE Transactions on Industrial Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9424\/10192510\/09980416.pdf?arnumber=9980416","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T18:12:25Z","timestamp":1692036745000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9980416\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":36,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tii.2022.3228383","relation":{},"ISSN":["1551-3203","1941-0050"],"issn-type":[{"value":"1551-3203","type":"print"},{"value":"1941-0050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]}}}