{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T09:06:13Z","timestamp":1771923973775,"version":"3.50.1"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,3,5]],"date-time":"2020-03-05T00:00:00Z","timestamp":1583366400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,3,5]],"date-time":"2020-03-05T00:00:00Z","timestamp":1583366400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Fuzzy Syst."],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s40815-020-00816-x","type":"journal-article","created":{"date-parts":[[2020,3,5]],"date-time":"2020-03-05T02:02:28Z","timestamp":1583373748000},"page":"891-900","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Interval Fuzzy c-Regression Models with Competitive Agglomeration for Symbolic Interval-Valued Data"],"prefix":"10.1007","volume":"22","author":[{"given":"Chen-Chia","family":"Chuang","sequence":"first","affiliation":[]},{"given":"Jin-Tsong","family":"Jeng","sequence":"additional","affiliation":[]},{"given":"Wei-Yang","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Chih-Ching","family":"Hsiao","sequence":"additional","affiliation":[]},{"given":"Chin-Wang","family":"Tao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,5]]},"reference":[{"key":"816_CR1","volume-title":"Symbolic data analysis: conceptual statistics and data mining","author":"L Billard","year":"2007","unstructured":"Billard, L., Diday, E.: Symbolic data analysis: conceptual statistics and data mining. Wiley, New York (2007)"},{"key":"816_CR2","unstructured":"Beranger, B., Lin, H., Sisson, S. A.: New models for symbolic data analysis, downloaded by arXiv.org (2018)"},{"key":"816_CR3","doi-asserted-by":"crossref","unstructured":"Bock, H.-H.: Probabilistic modeling for symbolic data. In: Proceedings in computational statistics (COMPSTAT 2008), pp. 55\u201365, (2008)","DOI":"10.1007\/978-3-7908-2084-3_5"},{"key":"816_CR4","doi-asserted-by":"publisher","DOI":"10.1002\/9781119010401","volume-title":"Clustering methodology for symbolic data","author":"L Billard","year":"2019","unstructured":"Billard, L., Diday, E.: Clustering methodology for symbolic data. Wiley, New York (2019)"},{"key":"816_CR5","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1002\/widm.1133","volume":"4","author":"P Brito","year":"2014","unstructured":"Brito, P.: Symbolic data analysis: another look at the interaction of data mining and statistics. Wires Data Mining Knowl. Discov. 4, 281\u2013295 (2014)","journal-title":"Wires Data Mining Knowl. Discov."},{"key":"816_CR6","unstructured":"Billard, L., Diday, E.: Regression analysis for interval-valued data. In: Data analysis, classification and related methods. Proceedings of the Seventh Conference of the International Federation of Classification Societies (IFCS\u201900), pp. 369\u2013374, Springer, Belgium, (2000)"},{"issue":"3","key":"816_CR7","doi-asserted-by":"publisher","first-page":"1500","DOI":"10.1016\/j.csda.2007.04.014","volume":"52","author":"EAL Neto","year":"2008","unstructured":"Neto, E.A.L., De Carvalho, F.A.T.: Centre and range method for fitting a linear regression model to symbolic interval data. Comput. Stat. Data Anal. 52(3), 1500\u20131515 (2008)","journal-title":"Comput. Stat. Data Anal."},{"key":"816_CR8","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/s11634-006-0003-7","volume":"1","author":"G Gonz\u00e1lez-Rodr\u00edguez","year":"2007","unstructured":"Gonz\u00e1lez-Rodr\u00edguez, G., Blanco, \u00c1., Corral, N., Colubi, A.: Least squares estimation of linear regression models for convex compact random sets. Adv. Data Anal. Classif. 1, 67\u201381 (2007)","journal-title":"Adv. Data Anal. Classif."},{"issue":"3","key":"816_CR9","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1016\/j.ijforecast.2010.02.012","volume":"27","author":"ALS Maia","year":"2011","unstructured":"Maia, A.L.S., De Carvalho, F.A.T.: Holt\u2019s exponential smoothing and neural network models for forecasting interval-valued time series. Int. J. Forecast. 27(3), 740\u2013759 (2011)","journal-title":"Int. J. Forecast."},{"key":"816_CR10","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1016\/j.neucom.2018.11.063","volume":"331","author":"Z Yang","year":"2019","unstructured":"Yang, Z., Lin, D.K., Zhang, A.: Interval-valued data prediction via regularized artificial neural network. Neurocomputing 331, 336\u2013345 (2019)","journal-title":"Neurocomputing"},{"issue":"3","key":"816_CR11","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1016\/j.ins.2007.09.015","volume":"178","author":"CC Chuang","year":"2008","unstructured":"Chuang, C.C.: Extended support vector interval regression networks for interval input-output data. Inf. Sci. 178(3), 871\u2013891 (2008)","journal-title":"Inf. Sci."},{"key":"816_CR12","doi-asserted-by":"crossref","unstructured":"Su, S. F., Chuang, C. C., Tao, C. W., Jeng, J. T., Hsiao, C. C.: Radial basis function networks with linear interval regression weights for symbolic interval data. In: IEEE Transaction Syst., Man. Cybern., Part B, vol. 42, no. 1, pp. 69\u201380 (2012)","DOI":"10.1109\/TSMCB.2011.2161468"},{"key":"816_CR13","unstructured":"de Carvalho F. A. T., Saporta, G., Queiroz, D. N.: A clusterwise center and range"},{"key":"816_CR14","unstructured":"Regression model for interval-valued data. In: 19th international conference on computational statistics, Paris France, August 22\u201327, 2010 Keynote, Invited and Contributed Papers"},{"key":"816_CR15","unstructured":"de Carvalho, F. A. T., Lima Neto, E. A.: Exponential-type kernel based robust regression for interval-valued data. In: Symbolic data analysis workshop (2018)"},{"issue":"3","key":"816_CR16","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1109\/91.236552","volume":"1","author":"RJ Hathaway","year":"1993","unstructured":"Hathaway, R.J., Bezdek, J.C.: Switching regression models and fuzzy clustering. IEEE Trans. Fuzzy Syst. 1(3), 195\u2013204 (1993)","journal-title":"IEEE Trans. Fuzzy Syst."},{"issue":"7","key":"816_CR17","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1016\/S0031-3203(96)00140-9","volume":"30","author":"H Frigui","year":"1997","unstructured":"Frigui, H., Krishnapuram, R.: Clustering by competitive agglomeration. Pattern Recogn. 30(7), 1109\u20131119 (1997)","journal-title":"Pattern Recogn."},{"key":"816_CR18","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.engappai.2009.02.003","volume":"22","author":"G Li","year":"2009","unstructured":"Li, G., Zhou, J., Xiang, X., Li, Q., An, X.: T-S fuzzy model identification based on a novel fuzzy C-regression model clustering algorithm. Eng. Appl. Artif. Intell. 22, 646\u2013653 (2009)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"816_CR19","doi-asserted-by":"crossref","unstructured":"Jacek, M.: \u03b5-insensitive fuzzy C-regression models: introduction to \u03b5-insensitive fuzzy modeling. In: IEEE Transaction Syst., Man. Cybern., Part B, vol. 34, no. 1, pp. 4\u201315 (2004)","DOI":"10.1109\/TSMCB.2002.804371"},{"key":"816_CR20","doi-asserted-by":"crossref","unstructured":"de Carvalho, F. A. T.: A clusterwise center and range regression model for interval-valued data. In: Proceeding of COMPSTAT\u20192010, (2010)","DOI":"10.1007\/978-3-7908-2604-3_45"},{"key":"816_CR21","doi-asserted-by":"publisher","DOI":"10.1002\/9780470061190","volume-title":"Advances in fuzzy clustering and its applications","author":"J Valente de Oliveira","year":"2007","unstructured":"Valente de Oliveira, J., Pedrycz, W.: Advances in fuzzy clustering and its applications. Wiley, New York (2007)"},{"key":"816_CR22","unstructured":"Neto, E. A. L., de Carvalho, F. A. T., Bezerra, L. X. T.: Linear regression methods to predict interval-valued data. In: Proceeding of the Ninth Brazilian symposium on neural networks, pp. 125\u2013130 (2006)"}],"container-title":["International Journal of Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40815-020-00816-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s40815-020-00816-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40815-020-00816-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T00:24:52Z","timestamp":1614903892000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s40815-020-00816-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,5]]},"references-count":22,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["816"],"URL":"https:\/\/doi.org\/10.1007\/s40815-020-00816-x","relation":{},"ISSN":["1562-2479","2199-3211"],"issn-type":[{"value":"1562-2479","type":"print"},{"value":"2199-3211","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,5]]},"assertion":[{"value":"3 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 January 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 March 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}