{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T04:13:00Z","timestamp":1744171980775,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":33,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642333613"},{"type":"electronic","value":"9783642333620"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"DOI":"10.1007\/978-3-642-33362-0_11","type":"book-chapter","created":{"date-parts":[[2012,9,11]],"date-time":"2012-09-11T12:21:22Z","timestamp":1347366082000},"page":"141-153","source":"Crossref","is-referenced-by-count":0,"title":["Navigating Interpretability Issues in Evolving Fuzzy Systems"],"prefix":"10.1007","author":[{"given":"Edwin","family":"Lughofer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Angelov, P., Filev, D.: Simpl_eTS: A simplified method for learning evolving Takagi-Sugeno fuzzy models. In: Proceedings of FUZZ-IEEE 2005, Reno, Nevada, U.S.A., pp. 1068\u20131073 (2005)","DOI":"10.1109\/FUZZY.2005.1452543"},{"key":"11_CR2","doi-asserted-by":"publisher","DOI":"10.1002\/9780470569962","volume-title":"Evolving Intelligent Systems \u2014 Methodology and Applications","author":"P. Angelov","year":"2010","unstructured":"Angelov, P., Filev, D., Kasabov, N.: Evolving Intelligent Systems \u2014 Methodology and Applications. John Wiley & Sons, New York (2010)"},{"key":"11_CR3","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1002\/9780470569962.ch2","volume-title":"Evolving Intelligent Systems: Methodology and Applications","author":"P.P. Angelov","year":"2010","unstructured":"Angelov, P.P.: Evolving Takagi-Sugeno fuzzy systems from streaming data, eTS+. In: Angelov, P., Filev, D., Kasabov, N. (eds.) Evolving Intelligent Systems: Methodology and Applications, pp. 21\u201350. John Wiley & Sons, New York (2010)"},{"issue":"1","key":"11_CR4","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1109\/TSMCB.2003.817053","volume":"34","author":"P.P. Angelov","year":"2004","unstructured":"Angelov, P.P., Filev, D.: An approach to online identification of Takagi-Sugeno fuzzy models. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics\u00a034(1), 484\u2013498 (2004)","journal-title":"IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics"},{"issue":"23","key":"11_CR5","doi-asserted-by":"publisher","first-page":"3160","DOI":"10.1016\/j.fss.2008.06.019","volume":"159","author":"P.P. Angelov","year":"2008","unstructured":"Angelov, P.P., Lughofer, E., Zhou, X.: Evolving fuzzy classifiers using different model architectures. Fuzzy Sets and Systems\u00a0159(23), 3160\u20133182 (2008)","journal-title":"Fuzzy Sets and Systems"},{"issue":"6","key":"11_CR6","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1109\/91.811237","volume":"7","author":"M. Bikdash","year":"1999","unstructured":"Bikdash, M.: A highly interpretable form of Sugeno inference systems. IEEE Transactions on Fuzzy Systems\u00a07(6), 686\u2013696 (1999)","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"11_CR7","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-37057-4","volume-title":"Interpretability Issues in Fuzzy Modeling","author":"J. Casillas","year":"2003","unstructured":"Casillas, J., Cordon, O., Herrera, F., Magdalena, L.: Interpretability Issues in Fuzzy Modeling. Springer, Heidelberg (2003)"},{"issue":"1","key":"11_CR8","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.fss.2010.08.006","volume":"163","author":"W.Y. Cheng","year":"2011","unstructured":"Cheng, W.Y., Juang, C.F.: An incremental support vector machine-trained ts-type fuzzy system for online classification problems. Fuzzy Sets and Systems\u00a0163(1), 24\u201344 (2011)","journal-title":"Fuzzy Sets and Systems"},{"key":"11_CR9","first-page":"845","volume":"5","author":"J.G. Dy","year":"2004","unstructured":"Dy, J.G., Brodley, C.E.: Feature selection for unsupervised learning. Journal of Machine Learning Research\u00a05, 845\u2013889 (2004)","journal-title":"Journal of Machine Learning Research"},{"key":"11_CR10","volume-title":"Intelligent Decision and Policy Making Support Systems","author":"J. Feng","year":"2008","unstructured":"Feng, J.: An intelligent decision support system based on machine learning and dynamic track of psychological evaluation criterion. In: Kacpzryk, J. (ed.) Intelligent Decision and Policy Making Support Systems. Springer, Heidelberg (2008)"},{"issue":"20","key":"11_CR11","doi-asserted-by":"publisher","first-page":"4340","DOI":"10.1016\/j.ins.2011.02.021","volume":"181","author":"M.J. Gacto","year":"2011","unstructured":"Gacto, M.J., Alcala, R., Herrera, F.: Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures. Information Sciences\u00a0181(20), 4340\u20134360 (2011)","journal-title":"Information Sciences"},{"issue":"1","key":"11_CR12","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/s12530-010-9004-z","volume":"1","author":"A. Kalhor","year":"2010","unstructured":"Kalhor, A., Araabi, B.N., Lucas, C.: An online predictor model as adaptive habitually linear and transiently nonlinear model. Evolving Systems\u00a01(1), 29\u201341 (2010)","journal-title":"Evolving Systems"},{"key":"11_CR13","volume-title":"Fault Diagnosis - Models, Artificial Intelligence and Applications","author":"J. Korbicz","year":"2004","unstructured":"Korbicz, J., Koscielny, J.M., Kowalczuk, Z., Cholewa, W.: Fault Diagnosis - Models, Artificial Intelligence and Applications. Springer, Heidelberg (2004)"},{"issue":"2","key":"11_CR14","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.fss.2004.03.001","volume":"150","author":"G. Leng","year":"2005","unstructured":"Leng, G., McGinnity, T.M., Prasad, G.: An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network. Fuzzy Sets and Systems\u00a0150(2), 211\u2013243 (2005)","journal-title":"Fuzzy Sets and Systems"},{"issue":"1","key":"11_CR15","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s12530-012-9045-6","volume":"3","author":"G. Leng","year":"2012","unstructured":"Leng, G., Zeng, X.-J., Keane, J.A.: An improved approach of self-organising fuzzy neural network based on similarity measures. Evolving Systems\u00a03(1), 19\u201330 (2012)","journal-title":"Evolving Systems"},{"key":"11_CR16","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1002\/9780470569962.ch4","volume-title":"Evolving Intelligent Systems: Methodology and Applications","author":"E. Lima","year":"2010","unstructured":"Lima, E., Hell, M., Ballini, R., Gomide, F.: Evolving fuzzy modeling using participatory learning. In: Angelov, P., Filev, D., Kasabov, N. (eds.) Evolving Intelligent Systems: Methodology and Applications, pp. 67\u201386. John Wiley & Sons, New York (2010)"},{"key":"11_CR17","volume-title":"System Identification: Theory for the User","author":"L. Ljung","year":"1999","unstructured":"Ljung, L.: System Identification: Theory for the User. Prentice Hall PTR, Prentic Hall Inc., Upper Saddle River, New Jersey (1999)"},{"key":"11_CR18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-18087-3","volume-title":"Evolving Fuzzy Systems \u2014 Methodologies, Advanced Concepts and Applications","author":"E. Lughofer","year":"2011","unstructured":"Lughofer, E.: Evolving Fuzzy Systems \u2014 Methodologies, Advanced Concepts and Applications. Springer, Heidelberg (2011)"},{"issue":"1","key":"11_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.fss.2010.08.012","volume":"163","author":"E. Lughofer","year":"2011","unstructured":"Lughofer, E.: On-line incremental feature weighting in evolving fuzzy classifiers. Fuzzy Sets and Systems\u00a0163(1), 1\u201323 (2011)","journal-title":"Fuzzy Sets and Systems"},{"issue":"3","key":"11_CR20","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/s12530-011-9032-3","volume":"2","author":"E. Lughofer","year":"2011","unstructured":"Lughofer, E., Bouchot, J.-L., Shaker, A.: On-line elimination of local redundancies in evolving fuzzy systems. Evolving Systems\u00a02(3), 165\u2013187 (2011)","journal-title":"Evolving Systems"},{"key":"11_CR21","volume-title":"Learning in Non-Stationary Environments: Methods and Applications","author":"E. Lughofer","year":"2012","unstructured":"Lughofer, E., Eitzinger, C., Guardiola, C.: On-line quality control with flexible evolving fuzzy systems. In: Sayed-Mouchaweh, M., Lughofer, E. (eds.) Learning in Non-Stationary Environments: Methods and Applications. Springer, New York (2012)"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Lughofer, E., H\u00fcllermeier, E.: On-line redundancy elimination in evolving fuzzy regression models using a fuzzy inclusion measure. In: Proceedings of the EUSFLAT 2011 Conference, Aix-Les-Bains, France, pp. 380\u2013387. Elsevier (2011)","DOI":"10.2991\/eusflat.2011.51"},{"key":"11_CR23","unstructured":"Lughofer, E., H\u00fcllermeier, E., Klement, E.P.: Improving the interpretability of data-driven evolving fuzzy systems. In: Proceedings of EUSFLAT 2005, Barcelona, Spain, pp. 28\u201333 (2005)"},{"key":"11_CR24","first-page":"55","volume":"7","author":"N.R. Pal","year":"1999","unstructured":"Pal, N.R., Pal, K.: Handling of inconsistent rules with an extended model of fuzzy reasoning. Journal of Intelligent and Fuzzy Systems\u00a07, 55\u201373 (1999)","journal-title":"Journal of Intelligent and Fuzzy Systems"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Ramos, J.V., Dourado, A.: Pruning for interpretability of large spanned eTS. In: Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems (EFS 2006), Lake District, UK, pp. 55\u201360 (2006)","DOI":"10.1109\/ISEFS.2006.251154"},{"key":"11_CR26","volume-title":"Learning in Non-Stationary Environments: Methods and Applications","author":"H.-J. Rong","year":"2012","unstructured":"Rong, H.-J.: Sequential adaptive fuzzy inference system for function approximation problems. In: Sayed-Mouchaweh, M., Lughofer, E. (eds.) Learning in Non-Stationary Environments: Methods and Applications. Springer, New York (2012)"},{"key":"11_CR27","unstructured":"Rosemann, N., Brockmann, W., Neumann, B.: Enforcing local properties in online learning first order TS-fuzzy systems by incremental regularization. In: Proceedings of IFSA-EUSFLAT 2009, Lisbon, Portugal, pp. 466\u2013471 (2009)"},{"key":"11_CR28","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-8020-5","volume-title":"Learning in Non-Stationary Environments: Methods and Applications","author":"M. Sayed-Mouchaweh","year":"2012","unstructured":"Sayed-Mouchaweh, M., Lughofer, E.: Learning in Non-Stationary Environments: Methods and Applications. Springer, New York (2012)"},{"issue":"1","key":"11_CR29","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.: Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man and Cybernetics\u00a015(1), 116\u2013132 (1985)","journal-title":"IEEE Transactions on Systems, Man and Cybernetics"},{"issue":"6","key":"11_CR30","doi-asserted-by":"publisher","first-page":"1439","DOI":"10.1109\/TFUZZ.2008.925918","volume":"16","author":"W. Wang","year":"2008","unstructured":"Wang, W., Vrbanek, J.: An evolving fuzzy predictor for industrial applications. IEEE Transactions on Fuzzy Systems\u00a016(6), 1439\u20131449 (2008)","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"11_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/3-540-39949-6_1","volume-title":"Medical Data Analysis","author":"T. Wetter","year":"2000","unstructured":"Wetter, T.: Medical Decision Support Systems. In: Brause, R., Hanisch, E. (eds.) ISMDA 2000. LNCS, vol.\u00a01933, pp. 1\u20133. Springer, Heidelberg (2000)"},{"issue":"4","key":"11_CR32","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/91.728447","volume":"6","author":"J. Yen","year":"1998","unstructured":"Yen, J., Wang, L., Gillespie, C.W.: Improving the interpretability of TSK fuzzy models by combining global learning and local learning. IEEE Transactions on Fuzzy Systems\u00a06(4), 530\u2013537 (1998)","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"23","key":"11_CR33","doi-asserted-by":"publisher","first-page":"3091","DOI":"10.1016\/j.fss.2008.05.016","volume":"159","author":"S.M. Zhou","year":"2008","unstructured":"Zhou, S.M., Gan, J.Q.: Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy systems modelling. Fuzzy Sets and Systems\u00a0159(23), 3091\u20133131 (2008)","journal-title":"Fuzzy Sets and Systems"}],"container-title":["Lecture Notes in Computer Science","Scalable Uncertainty Management"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-33362-0_11.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,8]],"date-time":"2025-04-08T06:17:59Z","timestamp":1744093079000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-33362-0_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"ISBN":["9783642333613","9783642333620"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-33362-0_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2012]]}}}