{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T20:23:06Z","timestamp":1776370986500,"version":"3.51.2"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2015,3,3]],"date-time":"2015-03-03T00:00:00Z","timestamp":1425340800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evolving Systems"],"published-print":{"date-parts":[[2016,3]]},"DOI":"10.1007\/s12530-015-9129-1","type":"journal-article","created":{"date-parts":[[2015,3,2]],"date-time":"2015-03-02T06:09:35Z","timestamp":1425276575000},"page":"1-14","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Evolving Takagi\u2013Sugeno model based on online Gustafson-Kessel algorithm and kernel recursive least square method"],"prefix":"10.1007","volume":"7","author":[{"given":"Soroosh","family":"Shafieezadeh-Abadeh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmad","family":"Kalhor","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,3,3]]},"reference":[{"issue":"1","key":"9129_CR1","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1109\/TSMCB.2003.817053","volume":"34","author":"PP Angelov","year":"2004","unstructured":"Angelov PP, Filev DP (2004) An approach to online identification of Takagi\u2013Sugeno fuzzy models. IEEE Trans Syst Man Cybern B 34(1):484\u2013498","journal-title":"IEEE Trans Syst Man Cybern B"},{"key":"9129_CR2","doi-asserted-by":"crossref","unstructured":"Angelov P, Filev D (2005) Simpl_eTS: a simplified method for learning evolving Takagi-Sugeno fuzzy models. In: Proceedings of IEEE international conference on fuzzy systems, pp 1068\u20131073","DOI":"10.1109\/FUZZY.2005.1452543"},{"key":"9129_CR3","doi-asserted-by":"crossref","unstructured":"Angelov P, Zhou X (2006) Evolving fuzzy systems from data streams in real-time. In: Proceedings of IEEE international symposium on evolving fuzzy systems, pp 29\u201335","DOI":"10.1109\/ISEFS.2006.251157"},{"key":"9129_CR4","doi-asserted-by":"crossref","unstructured":"Angelov P, Zhou X (2008) On line learning fuzzy rule-based system structure from data streams. In: Proceedings of IEEE international conference on fuzzy systems, pp 915\u2013922","DOI":"10.1109\/FUZZY.2008.4630479"},{"issue":"7","key":"9129_CR5","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.1088\/0957-0233\/17\/7\/020","volume":"17","author":"P Angelov","year":"2006","unstructured":"Angelov P, Giglio V, Guardiola C, Lughofer E, Luj\u00e1n JM (2006) An approach to model-based fault detection in industrial measurement systems with application to engine test benches. Meas Sci Technol 17(7):1809","journal-title":"Meas Sci Technol"},{"issue":"6","key":"9129_CR6","first-page":"461","volume":"1","author":"RD Baruah","year":"2011","unstructured":"Baruah RD, Angelov P (2011) Evolving fuzzy systems for data streams: a survey. Wiley Interdiscip Rev: Data Min Knowl Disc 1(6):461\u2013476","journal-title":"Wiley Interdiscip Rev: Data Min Knowl Disc"},{"issue":"2","key":"9129_CR7","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/0098-3004(84)90020-7","volume":"10","author":"JC Bezdek","year":"1984","unstructured":"Bezdek JC, Ehrlich R, Full W (1984) FCM: the fuzzy c-means clustering algorithm. Comput Geosci 10(2):191\u2013203","journal-title":"Comput Geosci"},{"issue":"1","key":"9129_CR8","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/S0016-0032(96)00059-2","volume":"334","author":"S Bittanti","year":"1997","unstructured":"Bittanti S, Piroddi L (1997) Nonlinear identification and control of a heat exchanger: a neural network approach. J Franklin Inst 334(1):135\u2013153","journal-title":"J Franklin Inst"},{"issue":"3","key":"9129_CR9","first-page":"273","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":"9129_CR10","unstructured":"DaISy (2014) Database for the identification of systems. http:\/\/www.esat.kuleuven.be\/sista\/daisy\/"},{"issue":"1","key":"9129_CR11","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s12530-010-9025-7","volume":"2","author":"D Dov\u017ean","year":"2011","unstructured":"Dov\u017ean D, \u0160krjanc I (2011) Recursive clustering based on a Gustafson-Kessel algorithm. Evol Syst 2(1):15\u201324","journal-title":"Evol Syst"},{"issue":"1","key":"9129_CR12","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1016\/j.asoc.2007.05.006","volume":"8","author":"H Du","year":"2008","unstructured":"Du H, Zhang N (2008) Application of evolving Takagi\u2013Sugeno fuzzy model to nonlinear system identification. Appl Soft Comput 8(1):676\u2013686","journal-title":"Appl Soft Comput"},{"issue":"8","key":"9129_CR13","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.1109\/TSP.2004.830985","volume":"52","author":"Y Engel","year":"2004","unstructured":"Engel Y, Mannor S, Meir R (2004) The kernel recursive least-squares algorithm. IEEE Trans Signal Process 52(8):2275\u20132285","journal-title":"IEEE Trans Signal Process"},{"key":"9129_CR14","doi-asserted-by":"crossref","unstructured":"Georgieva O, Filev D (2009) Gustafson-Kessel algorithm for evolving data stream clustering. In: Proceedings of the international conference on computer systems and technologies, pp 62:66","DOI":"10.1145\/1731740.1731807"},{"key":"9129_CR15","doi-asserted-by":"crossref","unstructured":"Gustafson DE, Kessel WC (1978) Fuzzy clustering with a fuzzy covariance matrix. In: Proceedings of IEEE conference on decision and control, pp 761\u2013766","DOI":"10.1109\/CDC.1978.268028"},{"issue":"1","key":"9129_CR16","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s12530-010-9004-z","volume":"1","author":"A Kalhor","year":"2010","unstructured":"Kalhor A, Araabi BN, Lucas C (2010) An online predictor model as adaptive habitually linear and transiently nonlinear model. Evol Syst 1(1):29\u201341","journal-title":"Evol Syst"},{"issue":"2","key":"9129_CR17","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1016\/j.eswa.2011.08.085","volume":"39","author":"A Kalhor","year":"2012","unstructured":"Kalhor A, Araabi BN, Lucas C (2012) A new systematic design for habitually linear evolving TS fuzzy model. Expert Syst Appl 39(2):1725\u20131736","journal-title":"Expert Syst Appl"},{"issue":"2","key":"9129_CR18","doi-asserted-by":"crossref","first-page":"939","DOI":"10.1016\/j.asoc.2012.09.015","volume":"13","author":"A Kalhor","year":"2013","unstructured":"Kalhor A, Araabi BN, Lucas C (2013) Evolving Takagi\u2013Sugeno fuzzy model based on switching to neighboring models. Appl Soft Comput 13(2):939\u2013946","journal-title":"Appl Soft Comput"},{"issue":"2","key":"9129_CR19","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/91.995117","volume":"10","author":"NK Kasabov","year":"2002","unstructured":"Kasabov NK, Song Q (2002) DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction. IEEE Trans Fuzzy Syst 10(2):144\u2013154","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"2","key":"9129_CR20","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/s12530-011-9043-0","volume":"3","author":"M Komijani","year":"2012","unstructured":"Komijani M, Lucas C, Araabi BN, Kalhor A (2012) Introducing evolving Takagi\u2013Sugeno method based on local least squares support vector machine models. Evol Syst 3(2):81\u201393","journal-title":"Evol Syst"},{"issue":"10","key":"9129_CR21","doi-asserted-by":"crossref","first-page":"3801","DOI":"10.1109\/TSP.2009.2022007","volume":"57","author":"W Liu","year":"2009","unstructured":"Liu W, Park IM, Wang Y, Principe JC (2009) Extended kernel recursive least squares algorithm. IEEE Trans Signal Process 57(10):3801\u20133814","journal-title":"IEEE Trans Signal Process"},{"key":"9129_CR22","doi-asserted-by":"crossref","DOI":"10.1002\/9780470608593","volume-title":"Kernel adaptive filtering: a comprehensive introduction","author":"W Liu","year":"2010","unstructured":"Liu W, Principe JC, Haykin S (2010) Kernel adaptive filtering: a comprehensive introduction. Wiley,\u00a0Hoboken"},{"issue":"6","key":"9129_CR23","doi-asserted-by":"crossref","first-page":"1393","DOI":"10.1109\/TFUZZ.2008.925908","volume":"16","author":"ED Lughofer","year":"2008","unstructured":"Lughofer ED (2008) FLEXFIS: a robust incremental learning approach for evolving Takagi\u2013Sugeno fuzzy models. IEEE Trans Fuzzy Syst 16(6):1393\u20131410","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"9129_CR24","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-18087-3","volume-title":"Evolving fuzzy systems\u2014methodologies, advanced concepts and applications","author":"E Lughofer","year":"2011","unstructured":"Lughofer E (2011) Evolving fuzzy systems\u2014methodologies, advanced concepts and applications. Springer, Heidelberg"},{"key":"9129_CR25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-3-642-14058-7_1","volume-title":"Information processing and management of uncertainty in knowledge-based systems. Applications","author":"E Lughofer","year":"2010","unstructured":"Lughofer E, Maci\u00e1n V, Guardiola C, Klement EP (2010) Data-driven design of Takagi\u2013Sugeno fuzzy systems for predicting NOx emissions. In: Information processing and management of uncertainty in knowledge-based systems. Applications. Springer, Berlin, Heidelberg, pp 1\u201310"},{"key":"9129_CR26","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/978-3-642-12686-4_5","volume-title":"Handbook of power systems II","author":"A Mu\u00f1oz","year":"2010","unstructured":"Mu\u00f1oz A, S\u00e1nchez-\u00dabeda E, Cruz A, Mar\u00edn J (2010) Short-term forecasting in power systems: a guided tour. In: Handbook of power systems II. Springer, Berlin, pp 129\u2013160"},{"key":"9129_CR27","doi-asserted-by":"crossref","unstructured":"Ngia LSH, Sjoberg J, Viberg M (1998) Adaptive neural nets filter using a recursive Levenberg-Marquardt search direction. In: Proceedings of the 32nd asilomar conference on signals, systems and computers, pp 697\u2013701","DOI":"10.1109\/ACSSC.1998.750952"},{"key":"9129_CR28","unstructured":"Petersen KB, Pedersen MS (2008) The matrix cookbook. Technical University of Denmark"},{"key":"9129_CR29","unstructured":"PJM (2014) PJM\u2014historical metered load data. http:\/\/www.pjm.com\/markets-and-operations\/ops-analysis\/historical-load-data.aspx"},{"key":"9129_CR30","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1007\/978-3-540-79547-6_17","volume-title":"Computer vision systems","author":"D Sannen","year":"2008","unstructured":"Sannen D, Nuttin M, Smith J, Tahir MA, Caleb-Solly P, Lughofer E, Eitzinger C (2008) An on-line interactive self-adaptive image classification framework. In: Computer vision systems. Springer, Berlin, pp 171\u2013180"},{"key":"9129_CR31","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/4175.001.0001","volume-title":"Learning with kernels: support vector machines, regularization, optimization, and beyond","author":"B Scholkopf","year":"2001","unstructured":"Scholkopf B, Smola AJ (2001) Learning with kernels: support vector machines, regularization, optimization, and beyond. MIT Press, Cambridge"},{"issue":"1","key":"9129_CR32","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/s12530-010-9006-x","volume":"1","author":"H Soleimani-B","year":"2010","unstructured":"Soleimani-B H, Lucas C, Araabi BN (2010) Recursive Gath-Geva clustering as a basis for evolving neuro-fuzzy modeling. Evol Syst 1(1):59\u201371","journal-title":"Evol Syst"},{"issue":"3","key":"9129_CR33","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/s10044-011-0203-4","volume":"15","author":"H Soleimani-B","year":"2012","unstructured":"Soleimani-B H, Lucas C, Araabi B (2012) Fast evolving neuro-fuzzy model and its application in online classification and time series prediction. Pattern Anal Appl 15(3):279\u2013288","journal-title":"Pattern Anal Appl"},{"issue":"1","key":"9129_CR34","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/S0893-6080(00)00077-0","volume":"14","author":"JAK Suykens","year":"2001","unstructured":"Suykens JAK, Vandewalle J, De Moor B (2001) Optimal control by least squares support vector machines. Neural Netw 14(1):23\u201335","journal-title":"Neural Netw"},{"key":"9129_CR35","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/TSMC.1985.6313399","volume":"15","author":"T Takagi","year":"1985","unstructured":"Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man Cybern 15:116\u2013132","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"9129_CR36","first-page":"211","volume":"1","author":"ME Tipping","year":"2001","unstructured":"Tipping ME (2001) Sparse Bayesian learning and the relevance vector machine. J Mach Learn Res 1:211\u2013244","journal-title":"J Mach Learn Res"},{"key":"9129_CR37","doi-asserted-by":"crossref","unstructured":"Van Vaerenbergh S, Via J, Santamaria I (2006) A sliding-window Kernel RLS algorithm and its application to nonlinear channel identification. In: Proceedings of IEEE international conference on\u00a0acoustics, speech and signal processing, pp\u00a0789\u2013792","DOI":"10.1109\/ICASSP.2006.1661394"}],"container-title":["Evolving Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-015-9129-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12530-015-9129-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-015-9129-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T15:46:12Z","timestamp":1747755972000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12530-015-9129-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,3]]},"references-count":37,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,3]]}},"alternative-id":["9129"],"URL":"https:\/\/doi.org\/10.1007\/s12530-015-9129-1","relation":{},"ISSN":["1868-6478","1868-6486"],"issn-type":[{"value":"1868-6478","type":"print"},{"value":"1868-6486","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,3,3]]}}}