{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T10:20:08Z","timestamp":1773656408989,"version":"3.50.1"},"reference-count":10,"publisher":"Pleiades Publishing Ltd","issue":"10","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Autom Remote Control"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1134\/s0005117921100143","type":"journal-article","created":{"date-parts":[[2021,11,22]],"date-time":"2021-11-22T05:02:57Z","timestamp":1637557377000},"page":"1774-1786","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Adaptation of the Structure and Parameters of Nonlinear Soft Sensors by the Example of an Industrial Reactive Distillation Process"],"prefix":"10.1134","volume":"82","author":[{"given":"O. Yu.","family":"Snegirev","sequence":"first","affiliation":[]},{"given":"A. Yu.","family":"Torgashov","sequence":"additional","affiliation":[]}],"member":"137","published-online":{"date-parts":[[2021,11,22]]},"reference":[{"key":"2193_CR1","doi-asserted-by":"publisher","first-page":"329","DOI":"10.6339\/JDS.2004.02(4).156","volume":"2","author":"S. Wang","year":"2004","unstructured":"Wang, S. and Murphy, M., Estimating optimal transformations for multiple\nregression using the ACE algorithm, J. Data Sci., 2004,\nvol. 2, pp. 329\u2013346.","journal-title":"J. Data Sci."},{"key":"2193_CR2","doi-asserted-by":"publisher","first-page":"199","DOI":"10.21307\/ijssis-2017-209","volume":"10","author":"T.A. AL-Qutami","year":"2017","unstructured":"AL-Qutami, T.A., Ibrahim, R., Ismail, I., and Ishak, M.A., Development of\nsoft sensor to estimate multiphase flow rates using neural networks and early stopping, Int. J. Smart Sensing Intell. Syst., 2017, vol. 10,\npp. 199\u2013222.","journal-title":"Int. J. Smart Sensing Intell. Syst."},{"key":"2193_CR3","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.chemolab.2018.07.002","volume":"180","author":"W. Zheng","year":"2018","unstructured":"Zheng, W., Liu, Y., Gao, Z., and Yang, J., Just-in-time semi-supervised soft\nsensor for quality prediction in industrial rubber mixers, Chemometrics Intell. Lab. Syst., 2018, vol. 180,\npp. 36\u201341.","journal-title":"Chemometrics Intell. Lab. Syst."},{"key":"2193_CR4","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1016\/j.cherd.2016.11.020","volume":"117","author":"W. Xiong","year":"2017","unstructured":"Xiong, W., Li, Y., Zhao, Y., and Huang, B., Adaptive soft sensor based on\ntime difference Gaussian process regression with local time-delay reconstruction, Chem. Eng. Res. Des., 2017, vol. 117,\npp. 670\u2013680.","journal-title":"Chem. Eng. Res. Des."},{"key":"2193_CR5","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.conengprac.2017.02.002","volume":"61","author":"L. Yao","year":"2017","unstructured":"Yao, L. and Ge, Z., Moving window adaptive soft sensor for state shifting\nprocess based on weighted supervised latent factor analysis, Control\nEng. Pract., 2017, vol. 61, pp. 72\u201380.","journal-title":"Control Eng. Pract."},{"key":"2193_CR6","doi-asserted-by":"publisher","first-page":"4738","DOI":"10.1021\/ie901098w","volume":"49(10)","author":"T.-H. Pan","year":"2010","unstructured":"Pan, T.-H., Wong, D.S.-H., and Jang, S.-S., Development of a novel soft\nsensor using a local model network with an adaptive subtractive clustering approach, Ind. & Eng. Chem. Res., 2010, vol. 49(10),\npp. 4738\u20134747.","journal-title":"Ind. & Eng. Chem. Res."},{"key":"2193_CR7","doi-asserted-by":"crossref","unstructured":"Snegirev, O.Yu. and Torgashov, A.Yu., Clustering-based development of an\nadaptive soft sensor for industrial rectification columns, Avtom.\nProm-sti, 2020, no. 8, pp. 44\u201350 (see pp. 1763\u20131773 in this issue of Autom. Remote Control for the English-language\nversion).","DOI":"10.1134\/S0005117921100131"},{"issue":"3","key":"2193_CR8","first-page":"127","volume":"32","author":"I.S. Mozharovskii","year":"2020","unstructured":"Mozharovskii, I.S., Samotylova, S.A., and Torgashov, A.Yu., Predictive\nmodeling of a mass-transfer technological plant using algorithm of alternating conditional\nexpectations, Mat. Model., 2020, vol. 32, no. 3,\npp. 127\u2013147.","journal-title":"Mat. Model."},{"key":"2193_CR9","unstructured":"Zhirkov, V.F., Sushkova, L.T., Korolev, A.I., Bol\u2019shakov, K.N., Obednin,\nA.A., and Prokof\u2019ev, G.V., Polynomial interpolation in digital signal processing with high\naccuracy requirements, Zh. Radioelektron. [Elektron. Zh.], 2017, no. 4, pp. 1\u201322."},{"key":"2193_CR10","doi-asserted-by":"publisher","first-page":"79","DOI":"10.3354\/cr030079","volume":"30","author":"C. Willmott","year":"2005","unstructured":"Willmott, C. and Matsuura, K., Advantages of the mean absolute error\n(MAE) over the root mean square error (RMSE) in assessing average model performance,\nClimate Res., 2005, vol. 30,\npp. 79\u201382.","journal-title":"Climate Res."}],"container-title":["Automation and Remote Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1134\/S0005117921100143.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1134\/S0005117921100143","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1134\/S0005117921100143.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:33:48Z","timestamp":1773614028000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1134\/S0005117921100143"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":10,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["2193"],"URL":"https:\/\/doi.org\/10.1134\/s0005117921100143","relation":{},"ISSN":["0005-1179","1608-3032"],"issn-type":[{"value":"0005-1179","type":"print"},{"value":"1608-3032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10]]},"assertion":[{"value":"11 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 January 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 March 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 November 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}