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Improving the interpretability of data-driven evolving fuzzy systems.

, , and . EUSFLAT Conf., page 28-33. Universidad Polytecnica de Catalunya, (2005)

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Fault detection in multi-sensor networks based on multivariate time-series models and orthogonal transformations., , , , , and . Information Fusion, (2014)Improving the interpretability of data-driven evolving fuzzy systems., , and . EUSFLAT Conf., page 28-33. Universidad Polytecnica de Catalunya, (2005)Reducing false positives for residual-based on-line fault detection by means of filters., , , , , and . SMC, page 2745-2750. IEEE, (2014)Editorial on the special issue "Hybrid and ensemble techniques in soft computing: recent advances and emerging trends"., , and . Soft Comput., 19 (12): 3353-3355 (2015)Editorial of the special issue: Online fuzzy machine learning and data mining., , and . Inf. Sci., (2013)Self-adaptive and local strategies for a smooth treatment of drifts in data streams., and . Evolving Systems, 5 (4): 239-257 (2014)Recent advances on evolving intelligent systems and applications., and . Evolving Systems, 5 (4): 217-218 (2014)Metacognitive learning approach for online tool condition monitoring., , , and . J. Intelligent Manufacturing, 30 (4): 1717-1737 (2019)DECMO2: a robust hybrid and adaptive multi-objective evolutionary algorithm., , , , and . Soft Comput., 19 (12): 3551-3569 (2015)Editorial: Special issue on Advanced Soft Computing for Prognostic Health Management., , , , , and . Appl. Soft Comput., (2018)