{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T08:05:54Z","timestamp":1775894754610,"version":"3.50.1"},"reference-count":46,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2019,2,3]],"date-time":"2019-02-03T00:00:00Z","timestamp":1549152000000},"content-version":"vor","delay-in-days":33,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71473201"],"award-info":[{"award-number":["71473201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004884","name":"Education Department of Sichuan Province","doi-asserted-by":"publisher","award":["17ZB0433"],"award-info":[{"award-number":["17ZB0433"]}],"id":[{"id":"10.13039\/501100004884","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2019,1]]},"abstract":"<jats:p>Crude oil is one of the most important types of energy for the global economy, and hence it is very attractive to understand the movement of crude oil prices. However, the sequences of crude oil prices usually show some characteristics of nonstationarity and nonlinearity, making it very challenging for accurate forecasting crude oil prices. To cope with this issue, in this paper, we propose a novel approach that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and extreme gradient boosting (XGBOOST), so\u2010called CEEMDAN\u2010XGBOOST, for forecasting crude oil prices. Firstly, we use CEEMDAN to decompose the nonstationary and nonlinear sequences of crude oil prices into several intrinsic mode functions (IMFs) and one residue. Secondly, XGBOOST is used to predict each IMF and the residue individually. Finally, the corresponding prediction results of each IMF and the residue are aggregated as the final forecasting results. To demonstrate the performance of the proposed approach, we conduct extensive experiments on the West Texas Intermediate (WTI) crude oil prices. The experimental results show that the proposed CEEMDAN\u2010XGBOOST outperforms some state\u2010of\u2010the\u2010art models in terms of several evaluation metrics.<\/jats:p>","DOI":"10.1155\/2019\/4392785","type":"journal-article","created":{"date-parts":[[2019,2,3]],"date-time":"2019-02-03T23:34:13Z","timestamp":1549236853000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["A CEEMDAN and XGBOOST\u2010Based Approach to Forecast Crude Oil Prices"],"prefix":"10.1155","volume":"2019","author":[{"given":"Yingrui","family":"Zhou","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1546-8015","authenticated-orcid":false,"given":"Taiyong","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jiayi","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Zijie","family":"Qian","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2019,2,3]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2017.09.010"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2008.05.003"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11293-008-9158-2"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-9883(00)00075-X"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2016.02.017"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2017.08.035"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2016.07.014"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1080\/10798587.2015.1092338"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30537-8_26"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2015.11.051"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.11.373"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.5897\/AJBM11.304"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2014.09.019"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.09.023"},{"key":"e_1_2_9_15_2","doi-asserted-by":"crossref","unstructured":"QiY.-L.andZhangW.-J. 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