{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T07:39:11Z","timestamp":1730273951327,"version":"3.28.0"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"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":[[2019,9]]},"DOI":"10.1109\/isgteurope.2019.8905631","type":"proceedings-article","created":{"date-parts":[[2019,11,25]],"date-time":"2019-11-25T18:52:22Z","timestamp":1574707942000},"page":"1-5","source":"Crossref","is-referenced-by-count":1,"title":["Comparison of Three Methods for a Weather Based Day-Ahead Load Forecasting"],"prefix":"10.1109","author":[{"given":"Mingzhe","family":"Zou","sequence":"first","affiliation":[]},{"given":"Jiachen","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Duo","family":"Fang","sequence":"additional","affiliation":[]},{"given":"Gareth","family":"Harrison","sequence":"additional","affiliation":[]},{"given":"Sasa","family":"Djokic","sequence":"additional","affiliation":[]},{"given":"Xinying","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chen","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Improving Neural Networks by Preventing Coadaptation of Feature Detectors","year":"2012","author":"hinton","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015435"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2004.843247"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1613\/jair.614"},{"journal-title":"Procs of the 12th Int Conf on Neural Information Processing Systems","article-title":"Boosting algorithms as gradient descent","year":"1999","author":"mason","key":"ref14"},{"journal-title":"A gentle tutorial of recurrent neural network with error backpropagation","year":"2016","author":"chen","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"ref17","article-title":"Training and analyzing deep recurrent neural networks","volume":"1","author":"hermans","year":"2013","journal-title":"Procs of the 26th Int Conf on Neural Information Processing Systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9045(76)90040-X"},{"key":"ref19","first-page":"22","article-title":"Modeling the Daily Temperature Cycle","volume":"57","author":"satterlund","year":"1983","journal-title":"Northwest Science"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.frl.2016.09.006"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCEP.2017.8004771"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2018.2851929"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2399311"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/PES.2005.1489152"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2013.2269803"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/9781118673362"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/497"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2017.2753802"},{"journal-title":"Analyzing the Sun's Path","year":"2016","author":"lesage","key":"ref20"},{"journal-title":"Moon Phases","year":"2019","author":"mahooti","key":"ref22"},{"key":"ref21","first-page":"1","article-title":"The lunar cycle: Effects on human and animal behavior and physiology","volume":"60","author":"zimecki","year":"2006","journal-title":"Adv in Hygiene and Exp Medicine"},{"journal-title":"Deep Learning","year":"2016","author":"goodfellow","key":"ref24"},{"journal-title":"Digital Design and computer Architecture","first-page":"712","year":"2012","author":"harris","key":"ref23"},{"journal-title":"A Survey of Forecast Error Measures","year":"2013","author":"shcherbakov","key":"ref26"},{"journal-title":"International Conference on Learning Representations","article-title":"Adam: A Method for Stochastic Optimization","year":"0","author":"kingma","key":"ref25"}],"event":{"name":"2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)","start":{"date-parts":[[2019,9,29]]},"location":"Bucharest, Romania","end":{"date-parts":[[2019,10,2]]}},"container-title":["2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8892271\/8905428\/08905631.pdf?arnumber=8905631","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T20:26:46Z","timestamp":1658262406000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8905631\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/isgteurope.2019.8905631","relation":{},"subject":[],"published":{"date-parts":[[2019,9]]}}}