{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:35:22Z","timestamp":1777613722018,"version":"3.51.4"},"reference-count":17,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,5]]},"DOI":"10.1109\/iwbis.2018.8471713","type":"proceedings-article","created":{"date-parts":[[2018,9,28]],"date-time":"2018-09-28T00:50:14Z","timestamp":1538095814000},"page":"43-48","source":"Crossref","is-referenced-by-count":20,"title":["Improving wind power prediction with retraining machine learning algorithms"],"prefix":"10.1109","author":[{"given":"Mariam","family":"Barque","sequence":"first","affiliation":[]},{"given":"Simon","family":"Martin","sequence":"additional","affiliation":[]},{"given":"Jeremie Etienne Norbert","family":"Vianin","sequence":"additional","affiliation":[]},{"given":"Dominique","family":"Genoud","sequence":"additional","affiliation":[]},{"given":"David","family":"Wannier","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2010.10.035"},{"key":"ref11","article-title":"Kaggle Competition: Product Classification","author":"he","year":"2015","journal-title":"Machine Learning CS933"},{"key":"ref12","article-title":"Solar production prediction based on nonlinear meteosource adaptation","author":"barque","year":"2015","journal-title":"IEEE IMIS Conference"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2013.07.001"},{"key":"ref14","year":"2016","journal-title":"Canton du Valais Production d’électricité"},{"key":"ref15","author":"xia","year":"2014","journal-title":"Gradient Boosting Machine for High-dimensional Additive Models"},{"key":"ref16","author":"dufour","year":"2017","journal-title":"Contribution à la mise au point d’un pilotage énergétique décentralisé par prédiction"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TEC.2008.2006552"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2006.879246"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2011.05.033"},{"key":"ref6","first-page":"105","author":"heinermann","year":"2016","journal-title":"Wind Power prediction with Machine Learning Ensembles"},{"key":"ref5","author":"giebel","year":"2003","journal-title":"The state-of-the-art in short-term prediction of wind power A literature overview"},{"key":"ref8","first-page":"6","article-title":"Data mining for wind power forecasting","author":"fugon","year":"2008","journal-title":"European Wind Energy Conference and Exhibition EWEC 2008"},{"key":"ref7","article-title":"Comparison of two new short-term wind-power forecasting systems","author":"sousa","year":"2008","journal-title":"Elsevier Journal of Renewable Energy"},{"key":"ref2","year":"2018","journal-title":"Market Data Day Ahead Auction"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/PMAPS.2016.7764085"},{"key":"ref1","year":"2017","journal-title":"Global Wind Statistics"}],"event":{"name":"2018 International Workshop on Big Data and Information Security (IWBIS)","location":"Jakarta","start":{"date-parts":[[2018,5,12]]},"end":{"date-parts":[[2018,5,13]]}},"container-title":["2018 International Workshop on Big Data and Information Security (IWBIS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8455507\/8471689\/08471713.pdf?arnumber=8471713","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T01:32:03Z","timestamp":1640223123000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8471713\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/iwbis.2018.8471713","relation":{},"subject":[],"published":{"date-parts":[[2018,5]]}}}