{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T21:11:13Z","timestamp":1773090673917,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,6,6]],"date-time":"2020-06-06T00:00:00Z","timestamp":1591401600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National natural science foundation of China (NSFC)","award":["61772176, 61402153"],"award-info":[{"award-number":["61772176, 61402153"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Due to the complexity of wind speed, it has been reported that mixed-noise models, constituted by multiple noise distributions, perform better than single-noise models. However, most existing regression models suppose that the noise distribution is single. Therefore, we study the Least square     S V R     of the Gaussian\u2013Laplacian mixed homoscedastic (    G L M \u2212 L S S V R    ) and heteroscedastic noise (    G L M H \u2212 L S S V R    ) for complicated or unknown noise distributions. The ALM technique is used to solve model     G L M \u2212 L S S V R    .     G L M \u2212 L S S V R     is used to predict short-term wind speed with historical data. The prediction results indicate that the presented model is superior to the single-noise model, and has fine performance.<\/jats:p>","DOI":"10.3390\/e22060629","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T04:19:39Z","timestamp":1591676379000},"page":"629","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["LSSVR Model of G-L Mixed Noise-Characteristic with Its Applications"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5047-8481","authenticated-orcid":false,"given":"Shiguang","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China"},{"name":"School of Computer Science and Technology, Tianjin University, Tianjin 300350, China"},{"name":"Engineering Lab of Intelligence Business and Internet of Things, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ting","family":"Zhou","sequence":"additional","affiliation":[{"name":"The State-Owned Assets Management Office, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4917-7651","authenticated-orcid":false,"given":"Lin","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China"},{"name":"Engineering Lab of Intelligence Business and Internet of Things, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baofang","family":"Chang","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,6]]},"reference":[{"key":"ref_1","unstructured":"Bishop, C.M. 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