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In this paper, we propose a new methodology for learning evolving fuzzy systems (EFS) from data streams in terms of on-line regression/system identification problems. It comes with enhanced dynamic complexity reduction steps, acting on model components and on the input structure and by employing generalized fuzzy rules in arbitrarily rotated position. It is thus termed as Gen-Smart-EFS (GS-EFS), short...
In this paper, we propose a new variant for incremental, evolving fuzzy systems extraction from data data streams, termed as GEN-FLEXFIS (short for Generalized Flexible Fuzzy Inference Systems). It builds upon the FLEXFIS methodology (published by the authors before) and extends it for generalized Takagi-Sugeno (TS) fuzzy systems, which implement generalized rotated rules in arbitrary position, employing...
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