{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T08:51:53Z","timestamp":1780995113954,"version":"3.54.1"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1109\/tnnls.2023.3259149","type":"journal-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T17:38:51Z","timestamp":1693503531000},"page":"11346-11358","source":"Crossref","is-referenced-by-count":72,"title":["ES-dRNN: A Hybrid Exponential Smoothing and Dilated Recurrent Neural Network Model for Short-Term Load Forecasting"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2548-6695","authenticated-orcid":false,"given":"Slawek","family":"Smyl","sequence":"first","affiliation":[{"name":"Facebook, Menlo Park, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2285-0327","authenticated-orcid":false,"given":"Grzegorz","family":"Dudek","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Częstochowa University of Technology, Częstochowa, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2609-811X","authenticated-orcid":false,"given":"Pawe\u0142","family":"Pe\u0142ka","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Częstochowa University of Technology, Częstochowa, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04130-y"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/59.801894"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2017.08.056"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2011.2161780"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2013.07.003"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2016.03.070"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2020.3018623"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2015.09.001"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2009.10.003"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09771"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1080\/00031305.2017.1380080"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2011.2162082"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2395822"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3533382"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.04.021"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2009.11.016"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2008.2008606"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-85099-9_16"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2844307"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2019.03.081"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2019.2943972"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2017.2753802"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2019.02.022"},{"key":"ref24","first-page":"1621","article-title":"Managing diversity in regression ensembles","volume":"6","author":"Brown","year":"2005","journal-title":"J. Mach. Learn. Res."},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2020.106265"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.117992"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2020.116415"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2020.3028133"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2020.3042389"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2019.03.017"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3046629"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2018.06.001"},{"key":"ref33","volume-title":"ES-dRNN Code and Data"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref36","first-page":"1","article-title":"Dilated recurrent neural networks","volume-title":"Proc. NIPS","author":"Chang"},{"key":"ref37","first-page":"1","article-title":"Sequence modeling using a memory controller extension for LSTM","volume-title":"Proc. NIPS","author":"Ben-Ari"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref39","first-page":"1231","article-title":"Nonparametric quantile estimation","volume":"7","author":"Takeuchi","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007379606734"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2017.08.005"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2018.01.045"},{"key":"ref43","first-page":"1","article-title":"Don\u2019t decay the learning rate, increase the batch size","volume-title":"Proc. ICLR","author":"Smith"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2015.07.035"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ijcnn52387.2021.9534134"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9206895"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67220-5_4"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403118"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2019.07.001"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.21437\/SSW.2016"},{"key":"ref51","first-page":"1","article-title":"N-BEATS: Neural basis expansion analysis for interpretable time series forecasting","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Oreshkin"},{"key":"ref52","first-page":"1","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ke"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1111\/j.1468-0262.2006.00718.x"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.116983"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/10623582\/10236525.pdf?arnumber=10236525","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T10:23:47Z","timestamp":1722939827000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10236525\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":55,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2023.3259149","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8]]}}}