{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:19:27Z","timestamp":1763201967460,"version":"3.37.3"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/linproxy.fan.workers.dev:443\/http\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["HIT.IBRSEM.201307","2014RFXXJ065"],"award-info":[{"award-number":["HIT.IBRSEM.201307","2014RFXXJ065"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Program for Harbin City Science and Technology Innovation Talents of Special Fund Project","award":["HIT.IBRSEM.201307","2014RFXXJ065"],"award-info":[{"award-number":["HIT.IBRSEM.201307","2014RFXXJ065"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2016]]},"abstract":"<jats:p>Diabetes is a serious threat to human health. Thus, research on noninvasive blood glucose detection has become crucial locally and abroad. Near-infrared transmission spectroscopy has important applications in noninvasive glucose detection. Extracting useful information and selecting appropriate modeling methods can improve the robustness and accuracy of models for predicting blood glucose concentrations. Therefore, an improved signal reconstruction and calibration modeling method is proposed in this study. On the basis of improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and correlative coefficient, the sensitive intrinsic mode functions are selected to reconstruct spectroscopy signals for developing the calibration model using the support vector regression (SVR) method. The radial basis function kernel is selected for SVR, and three parameters, namely, insensitive loss coefficient<mml:math xmlns:mml=\"https:\/\/linproxy.fan.workers.dev:443\/http\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mrow><mml:mi mathvariant=\"normal\">\u03b5<\/mml:mi><\/mml:mrow><\/mml:math>, penalty parameter<mml:math xmlns:mml=\"https:\/\/linproxy.fan.workers.dev:443\/http\/www.w3.org\/1998\/Math\/MathML\" id=\"M2\"><mml:mrow><mml:mi>C<\/mml:mi><\/mml:mrow><\/mml:math>, and width coefficient<mml:math xmlns:mml=\"https:\/\/linproxy.fan.workers.dev:443\/http\/www.w3.org\/1998\/Math\/MathML\" id=\"M3\"><mml:mrow><mml:mi mathvariant=\"normal\">\u03b3<\/mml:mi><\/mml:mrow><\/mml:math>, are identified beforehand for the corresponding model. Particle swarm optimization (PSO) is employed to optimize the simultaneous selection of the three parameters. Results of the comparison experiments using PSO-SVR and partial least squares show that the proposed signal reconstitution method is feasible and can eliminate noise in spectroscopy signals. The prediction accuracy of model using PSO-SVR method is also found to be better than that of other methods for near-infrared noninvasive glucose detection.<\/jats:p>","DOI":"10.1155\/2016\/8301962","type":"journal-article","created":{"date-parts":[[2016,8,22]],"date-time":"2016-08-22T21:01:18Z","timestamp":1471899678000},"page":"1-9","source":"Crossref","is-referenced-by-count":21,"title":["Improved CEEMDAN and PSO-SVR Modeling for Near-Infrared Noninvasive Glucose Detection"],"prefix":"10.1155","volume":"2016","author":[{"given":"Xiaoli","family":"Li","sequence":"first","affiliation":[{"name":"School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China"}]},{"ORCID":"https:\/\/linproxy.fan.workers.dev:443\/https\/orcid.org\/0000-0002-7462-6415","authenticated-orcid":true,"given":"Chengwei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China"}]}],"member":"311","reference":[{"key":"1","first-page":"1","volume":"18","year":"2015","journal-title":"Journal of Experimental Zoology, India"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/s0140-6736(09)60109-4"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1177\/000456329803500108"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/jssc.2014.2384037"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1364\/ao.42.000745"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1364\/ao.38.002916"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1089\/15209150050025168"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1364\/ol.31.000332"},{"issue":"1","key":"21","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1089\/152091500316683","volume":"2","year":"2000","journal-title":"Diabetes Technology and Therapeutics"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.3964\/j.issn.1000-0593(2012)10-2815-05"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1142\/s1793536910000422"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2014.06.009"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1109\/tim.2007.907967"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.3390\/e17106683"},{"first-page":"1","volume-title":"Chemometrics in analytical chemistry","year":"1994","key":"30"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.1142\/S1793536910000367"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1016\/j.aca.2004.12.024"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/linproxy.fan.workers.dev:443\/http\/downloads.hindawi.com\/journals\/cmmm\/2016\/8301962.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/linproxy.fan.workers.dev:443\/http\/downloads.hindawi.com\/journals\/cmmm\/2016\/8301962.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/linproxy.fan.workers.dev:443\/http\/downloads.hindawi.com\/journals\/cmmm\/2016\/8301962.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,17]],"date-time":"2020-05-17T03:46:03Z","timestamp":1589687163000},"score":1,"resource":{"primary":{"URL":"https:\/\/linproxy.fan.workers.dev:443\/http\/www.hindawi.com\/journals\/cmmm\/2016\/8301962\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":17,"alternative-id":["8301962","8301962"],"URL":"https:\/\/linproxy.fan.workers.dev:443\/https\/doi.org\/10.1155\/2016\/8301962","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"type":"print","value":"1748-670X"},{"type":"electronic","value":"1748-6718"}],"subject":[],"published":{"date-parts":[[2016]]}}}