{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T16:52:14Z","timestamp":1767977534896,"version":"3.49.0"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,2,25]],"date-time":"2021-02-25T00:00:00Z","timestamp":1614211200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>This paper proposes the use of a regularized mixture of linear experts (MoLE) for predictive modeling in multimode-multiphase industrial processes. For this purpose, different regularized MoLE were evaluated, namely, through the elastic net (EN), Lasso, and ridge regression (RR) penalties. Their performances were compared when trained with different numbers of samples, and in comparison to other nonlinear predictive models. The models were evaluated on real multiphase polymerization process data. The Lasso penalty provided the best performance among all regularizers for MoLE, even when trained with a small number of samples.<\/jats:p>","DOI":"10.3390\/app11052040","type":"journal-article","created":{"date-parts":[[2021,2,25]],"date-time":"2021-02-25T21:16:53Z","timestamp":1614287813000},"page":"2040","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Regularized Mixture of Linear Experts for Quality Prediction in Multimode and Multiphase Industrial Processes"],"prefix":"10.3390","volume":"11","author":[{"given":"Francisco","family":"Souza","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Institute of Systems and Robotics, University of Coimbra, P\u00f3lo II, PT-3030-290 Coimbra, Portugal"},{"name":"Department of Analytical Chemistry &amp; Chemometrics, Radboud University, 6525 AJ Nijmegen, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4616-3473","authenticated-orcid":false,"given":"J\u00e9r\u00f4me","family":"Mendes","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Institute of Systems and Robotics, University of Coimbra, P\u00f3lo II, PT-3030-290 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1007-8675","authenticated-orcid":false,"given":"Rui","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Institute of Systems and Robotics, University of Coimbra, P\u00f3lo II, PT-3030-290 Coimbra, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,25]]},"reference":[{"key":"ref_1","unstructured":"Fortuna, L., Graziani, S., and Xibilia, M.G. 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