RT Journal Article ID 31858a156fbad44a A1 Shtovba, Sergey D. T1 Ensuring Accuracy and Transparency of Mamdani Fuzzy Model in Learning by Experimental Data JF Journal of Automation and Information Sciences JO JAI(S) YR 2007 FD 2007-10-01 VO 39 IS 8 SP 39 OP 52 AB Typical violations of transparency of the Mamdani fuzzy model, which arise as a side effect of learning by experimental data are revealed. We suggest a new learning scheme of the Mamdani fuzzy model, which differs from the known ones by the following: 1) expansion of bearers of fuzzy sets of output variables; 2) excluding coordinates of maxima of belonging functions of extreme terms from the list of parameters to be tuned; 3) introducing constraints for linear ordering of fuzzy sets within limits of one term-set. Computer simulations indicate that learning by the new scheme does not break transparency of a fuzzy model. Moreover, accuracy of fuzzy model is not worse than for the case of typical learning. PB Begell House LK https://www.dl.begellhouse.com/journals/2b6239406278e43e,2aed04617948f36a,31858a156fbad44a.html