{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T02:06:48Z","timestamp":1776132408411,"version":"3.50.1"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T00:00:00Z","timestamp":1664409600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T00:00:00Z","timestamp":1664409600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72071008"],"award-info":[{"award-number":["72071008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71771011"],"award-info":[{"award-number":["71771011"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1007\/s12652-022-04385-9","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T03:37:46Z","timestamp":1664422666000},"page":"12949-12958","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["An uncertain support vector machine based on soft margin method"],"prefix":"10.1007","volume":"14","author":[{"given":"Qiqi","family":"Li","sequence":"first","affiliation":[]},{"given":"Zhongfeng","family":"Qin","sequence":"additional","affiliation":[]},{"given":"Zhe","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,29]]},"reference":[{"key":"4385_CR1","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1145\/130385.130401","volume-title":"Fifth annual workshop on computational learning theory","author":"B Boser","year":"1992","unstructured":"Boser B, Guyon I, Vapnik V (1992) A training algorithm for optimal margin classifiers. In: Fifth annual workshop on computational learning theory, vol 5. ACM, Pittsburgh, pp 144\u2013152","edition":"5"},{"issue":"2","key":"4385_CR2","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"C Burges","year":"1998","unstructured":"Burges C (1998) A tutorial on support vector machines for pattern recognition. Data Min Knowl Discov 2(2):121\u2013167","journal-title":"Data Min Knowl Discov"},{"key":"4385_CR3","doi-asserted-by":"publisher","first-page":"16803","DOI":"10.1007\/s00500-020-04973-x","volume":"24","author":"D Chen","year":"2020","unstructured":"Chen D (2020) Tukey\u2019s biweight estimation for uncertain regression model with imprecise observations. Soft Comput 24:16803\u201316809","journal-title":"Soft Comput"},{"issue":"3","key":"4385_CR4","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273\u2013297","journal-title":"Mach Learn"},{"key":"4385_CR5","doi-asserted-by":"publisher","first-page":"2655","DOI":"10.1007\/s00500-019-03821-x","volume":"24","author":"L Fang","year":"2020","unstructured":"Fang L, Hong Y (2020) Uncertain revised regression analysis with responses of logarithmic, square root and reciprocal transformations. Soft Comput 24:2655\u20132670","journal-title":"Soft Comput"},{"key":"4385_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-02965-9","author":"N Gautam","year":"2021","unstructured":"Gautam N, Singh A, Kumar K et al (2021) Investigation on performance analysis of support vector machine for classification of abnormal regions in medical image. J Ambient Intell Human Comput. https:\/\/doi.org\/10.1007\/s12652-021-02965-9","journal-title":"J Ambient Intell Human Comput"},{"key":"4385_CR7","doi-asserted-by":"publisher","first-page":"2543","DOI":"10.1007\/s00500-018-3611-1","volume":"24","author":"Z Hu","year":"2020","unstructured":"Hu Z, Gao J (2020) Uncertain Gompertz regression model with imprecise observations. Soft Comput 24:2543\u20132549","journal-title":"Soft Comput"},{"key":"4385_CR8","doi-asserted-by":"publisher","first-page":"3403","DOI":"10.3233\/JIFS-212156","volume":"43","author":"Q Li","year":"2022","unstructured":"Li Q, Qin Z, Liu Z (2022) Uncertain support vector regression with imprecise observations. J Intell Fuzzy Syst 43:3403\u20133409","journal-title":"J Intell Fuzzy Syst"},{"issue":"1","key":"4385_CR9","doi-asserted-by":"publisher","first-page":"2150008","DOI":"10.1142\/S1752890921500082","volume":"14","author":"W Lio","year":"2021","unstructured":"Lio W (2021) Uncertain statistics and COVID-19 spread in China. J Uncertain Syst 14(1):2150008","journal-title":"J Uncertain Syst"},{"issue":"2","key":"4385_CR10","doi-asserted-by":"publisher","first-page":"2573","DOI":"10.3233\/JIFS-18353","volume":"35","author":"W Lio","year":"2018","unstructured":"Lio W, Liu B (2018) Residual and confidence interval for uncertain regression model with imprecise observations. J Intell Fuzzy Syst 35(2):2573\u20132583","journal-title":"J Intell Fuzzy Syst"},{"key":"4385_CR11","doi-asserted-by":"publisher","first-page":"9351","DOI":"10.1007\/s00500-020-04951-3","volume":"24","author":"W Lio","year":"2020","unstructured":"Lio W, Liu B (2020) Uncertain maximum likelihood estimation with application to uncertain regression analysis. Soft Comput 24:9351\u20139360","journal-title":"Soft Comput"},{"key":"4385_CR12","volume-title":"Uncertainty theory","author":"B Liu","year":"2007","unstructured":"Liu B (2007) Uncertainty theory, 2nd edn. Springer, Berlin","edition":"2"},{"issue":"1","key":"4385_CR13","first-page":"3","volume":"3","author":"B Liu","year":"2009","unstructured":"Liu B (2009) Some research problems in uncertainty theory. J Uncertain Syst 3(1):3\u201310","journal-title":"J Uncertain Syst"},{"key":"4385_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13959-8","volume-title":"Uncertainty theory: a branch of mathematics for modeling human uncertainty","author":"B Liu","year":"2010","unstructured":"Liu B (2010) Uncertainty theory: a branch of mathematics for modeling human uncertainty. Springer, Berlin"},{"key":"4385_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44354-5","volume-title":"Uncertainty theory","author":"B Liu","year":"2015","unstructured":"Liu B (2015) Uncertainty theory, 4th edn. Springer, Berlin","edition":"4"},{"key":"4385_CR16","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s10700-019-09312-w","volume":"19","author":"Z Liu","year":"2020","unstructured":"Liu Z, Yang Y (2020) Least absolute deviations uncertain regression with imprecise observations. Fuzzy Optim Decis Mak 19:33\u201352","journal-title":"Fuzzy Optim Decis Mak"},{"issue":"5","key":"4385_CR17","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1080\/03081079.2020.1748616","volume":"49","author":"J Lu","year":"2020","unstructured":"Lu J, Peng J, Chen J et al (2020) Prediction method of autoregressive moving average models for uncertain time series. Int J Gen Syst 49(5):546\u2013572","journal-title":"Int J Gen Syst"},{"key":"4385_CR18","first-page":"1702","volume-title":"Proceedings of the 2002 international joint conference on neural networks","author":"S Mukkamala","year":"2002","unstructured":"Mukkamala S, Janoski G, Sung A (2002) Intrusion detection using neural networks and support vector machines. In: Proceedings of the 2002 international joint conference on neural networks, vol 2, pp 1702\u20131707","edition":"2"},{"key":"4385_CR19","doi-asserted-by":"publisher","first-page":"107298","DOI":"10.1016\/j.patcog.2020.107298","volume":"103","author":"O Okwuashi","year":"2020","unstructured":"Okwuashi O, Ndehedehe C (2020) Deep support vector machine for hyperspectral image classification. Pattern Recognit 103:107298","journal-title":"Pattern Recognit"},{"key":"4385_CR20","doi-asserted-by":"publisher","first-page":"5225","DOI":"10.1007\/s12652-020-02000-3","volume":"12","author":"N Priyadharsini","year":"2021","unstructured":"Priyadharsini N, Chitra D (2021) A kernel support vector machine based anomaly detection using spatio-temporal motion pattern models in extremely crowded scenes. J Ambient Intell Human Comput 12:5225\u20135234","journal-title":"J Ambient Intell Human Comput"},{"key":"4385_CR21","unstructured":"Qin Z, Li Q (2022) An uncertain support vector machine with imprecise observations. Technical Report"},{"key":"4385_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The nature of statistical learning theory","author":"V Vapnik","year":"1995","unstructured":"Vapnik V (1995) The nature of statistical learning theory. Springer, New York"},{"issue":"5","key":"4385_CR23","doi-asserted-by":"publisher","first-page":"988","DOI":"10.1109\/72.788640","volume":"10","author":"V Vapnik","year":"1999","unstructured":"Vapnik V (1999) An overview of statistical learning theory. IEEE Trans Neural Netw 10(5):988\u2013999","journal-title":"IEEE Trans Neural Netw"},{"key":"4385_CR24","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-019-01192-7","author":"P VenkateswarLal","year":"2019","unstructured":"VenkateswarLal P, Nitta G, Prasad A (2019) Ensemble of texture and shape descriptors using support vector machine classification for face recognition. J Ambient Intell Human Comput. https:\/\/doi.org\/10.1007\/s12652-019-01192-7","journal-title":"J Ambient Intell Human Comput"},{"key":"4385_CR25","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1007\/s12652-017-0538-9","volume":"8","author":"Y Wang","year":"2017","unstructured":"Wang Y, Luo S, Gao J (2017) Uncertain extensive game with application to resource allocation of national security. J Ambient Intell Human Comput 8:797\u2013808","journal-title":"J Ambient Intell Human Comput"},{"issue":"2","key":"4385_CR26","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1016\/j.ejor.2017.12.001","volume":"267","author":"H Wang","year":"2018","unstructured":"Wang H, Zheng B, Yoon S et al (2018) A support vector machine-based ensemble algorithm for breast cancer diagnosis. Eur J Oper Res 267(2):687\u2013699","journal-title":"Eur J Oper Res"},{"issue":"6","key":"4385_CR27","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1080\/03081079.2021.1950150","volume":"50","author":"Y Xin","year":"2021","unstructured":"Xin Y, Yang X, Gao J (2021) Least squares estimation for the high-order uncertain moving average model with application to carbon dioxide emissions. Int J Gen Syst 50(6):724\u2013740","journal-title":"Int J Gen Syst"},{"issue":"4","key":"4385_CR28","doi-asserted-by":"publisher","first-page":"819","DOI":"10.1109\/TFUZZ.2015.2486809","volume":"24","author":"X Yang","year":"2016","unstructured":"Yang X, Gao J (2016) Linear-quadratic uncertain differential game with application to resource extraction problem. IEEE Trans Fuzzy Syst 24(4):819\u2013826","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"3","key":"4385_CR29","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1007\/s10700-018-9298-z","volume":"18","author":"X Yang","year":"2019","unstructured":"Yang X, Liu B (2019) Uncertain time series analysis with imprecise observations. Fuzzy Optim Decis Mak 18(3):263\u2013278","journal-title":"Fuzzy Optim Decis Mak"},{"issue":"1","key":"4385_CR30","doi-asserted-by":"publisher","first-page":"2150001","DOI":"10.1142\/S175289092150001X","volume":"14","author":"K Yao","year":"2021","unstructured":"Yao K (2021) An uncertain single-server queueing model. J Uncertain Syst 14(1):2150001","journal-title":"J Uncertain Syst"},{"issue":"17","key":"4385_CR31","doi-asserted-by":"publisher","first-page":"5579","DOI":"10.1007\/s00500-017-2521-y","volume":"22","author":"K Yao","year":"2018","unstructured":"Yao K, Liu B (2018) Uncertain regression analysis: an approach for imprecise observations. Soft Comput 22(17):5579\u20135582","journal-title":"Soft Comput"},{"issue":"4","key":"4385_CR32","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1080\/03081079.2020.1748615","volume":"49","author":"C Zhang","year":"2020","unstructured":"Zhang C, Liu Z, Liu J (2020) Least absolute deviations for uncertain multivariate regression model. Int J Gen Syst 49(4):449\u2013465","journal-title":"Int J Gen Syst"},{"key":"4385_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10700-021-09355-y","volume":"20","author":"Y Zhang","year":"2021","unstructured":"Zhang Y, Gao J, Li X et al (2021) Two-person cooperative uncertain differential game with transferable payoffs. Fuzzy Optim Decis Making 20:1\u201328","journal-title":"Fuzzy Optim Decis Making"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04385-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-022-04385-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-04385-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T03:58:00Z","timestamp":1744171080000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-022-04385-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,29]]},"references-count":33,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2023,9]]}},"alternative-id":["4385"],"URL":"https:\/\/doi.org\/10.1007\/s12652-022-04385-9","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,29]]},"assertion":[{"value":"12 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 June 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 September 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The author declares that there is no conflict of interests regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This work did not involve any active collection of human data.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics statement"}}]}}