{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T14:43:29Z","timestamp":1777128209082,"version":"3.51.4"},"reference-count":40,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T00:00:00Z","timestamp":1704672000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:p>In this article, a novel approach is presented for drift\u2010aware feature learning aimed at calibrating drift biases in soft sensors for long\u2010term use. The proposed method leverages an autoencoder for data preprocessing to extract expressive signal drift traces features, and incorporates drift characteristics through the latent space representation in a long short\u2010term memory (LSTM) regression neural network. In the results, it is demonstrated that the proposed approach outperforms other typical recurrent neural networks, such as LSTM, gated recurrent unit, and bidirectional LSTM, with a reduced root mean square error of 60% for the training dataset (\u22482.5\u2009h) and 80% for the testing dataset (\u224820\u2009h). The proposed approach has the potential to optimize the performance of soft sensors with long\u2010term drift and reduce the need for frequent recalibration. By compensating for sensor drift using existing prior information and limited time data, the proposed neural network can effectively reduce the complexity and computational burden of the system, without the need for additional settings or hyperparameter fine\u2010tuning.<\/jats:p>","DOI":"10.1002\/aisy.202300486","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T22:12:49Z","timestamp":1704751969000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Drift\u2010Aware Feature Learning Based on Autoencoder Preprocessing for Soft Sensors"],"prefix":"10.1002","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8835-7896","authenticated-orcid":false,"given":"Junming","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering The Chinese University of Hong Kong  Hong Kong SAR 999077 China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9475-8677","authenticated-orcid":false,"given":"Jing","family":"Shu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The Chinese University of Hong Kong  Hong Kong SAR 999077 China"}]},{"given":"Md Masruck","family":"Alam","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The Chinese University of Hong Kong  Hong Kong SAR 999077 China"}]},{"given":"Zhaoli","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The Chinese University of Hong Kong  Hong Kong SAR 999077 China"}]},{"given":"Zheng","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The Chinese University of Hong Kong  Hong Kong SAR 999077 China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4375-653X","authenticated-orcid":false,"given":"Raymond Kai\u2010Yu","family":"Tong","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The Chinese University of Hong Kong  Hong Kong SAR 999077 China"}]}],"member":"311","published-online":{"date-parts":[[2024,1,8]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2012.2200790"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1021\/acsaelm.0c00278"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sna.2015.06.007"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1039\/C9SM01046G"},{"key":"e_1_2_10_6_1","first-page":"1","volume-title":"2022 IEEE\u2010EMBS Int. Conf. on Wearable and Implantable Body Sensor Networks (BSN)","author":"Shu J.","year":"2022"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/s22207705"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/s23136189"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/aisy.201900171"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/0079-6700(94)00001-I"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.crci.2006.07.008"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.sna.2020.112433"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.3390\/polym15102410"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aaz9239"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aav1488"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1002\/aisy.201900178"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2023.02.003"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3231849"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1089\/soro.2021.0012"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-021-01810-2"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jobe.2023.105961"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/s22207696"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"e_1_2_10_25_1","volume":"32","author":"Spielberg A.","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"e_1_2_10_26_1","unstructured":"M.Lewis Y.Liu N.Goyal M.Ghazvininejad A.Mohamed O.Levy V.Stoyanov L.Zettlemoyer arXiv:1910.13461 2019."},{"key":"e_1_2_10_27_1","first-page":"1","volume-title":"2018 Wireless Telecommunications Symposium (WTS)","author":"Chen Z.","year":"2018"},{"key":"e_1_2_10_28_1","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1007\/978-3-642-21735-7_6","volume-title":"Artificial Neural Networks and Machine Learning\u2013ICANN 2011: 21st Inter. Conf. on Artificial Neural Networks, Espoo, Finland, June 14\u201317, 2011, Proceedings, Part I 21","author":"Hinton G. E.","year":"2011"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"e_1_2_10_30_1","volume-title":"Deep Learning","author":"Goodfellow I.","year":"2016"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.08.043"},{"key":"e_1_2_10_32_1","first-page":"12","volume":"11","author":"Vincent P.","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_2_10_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cej.2018.12.025"},{"key":"e_1_2_10_34_1","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"e_1_2_10_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80056-5"},{"key":"e_1_2_10_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0042-6989(97)00169-7"},{"key":"e_1_2_10_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2014.2320500"},{"key":"e_1_2_10_38_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco_a_01199"},{"key":"e_1_2_10_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2976320"},{"key":"e_1_2_10_40_1","unstructured":"D. P.Kingma J.Ba arXiv:1412.6980 2014."},{"key":"e_1_2_10_41_1","doi-asserted-by":"publisher","DOI":"10.3390\/polym15143082"}],"container-title":["Advanced Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/aisy.202300486","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T22:47:05Z","timestamp":1759877225000},"score":1,"resource":{"primary":{"URL":"https:\/\/advanced.onlinelibrary.wiley.com\/doi\/10.1002\/aisy.202300486"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,8]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["10.1002\/aisy.202300486"],"URL":"https:\/\/doi.org\/10.1002\/aisy.202300486","archive":["Portico"],"relation":{},"ISSN":["2640-4567","2640-4567"],"issn-type":[{"value":"2640-4567","type":"print"},{"value":"2640-4567","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,8]]},"assertion":[{"value":"2023-08-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-01-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2300486"}}