By Jorge Casillas, O. Cordón, Francisco Herrera Triguero, Luis Magdalena
Fuzzy modeling has develop into the most efficient and profitable result of fuzzy common sense. between others, it's been utilized to wisdom discovery, automated class, long term prediction, or scientific and engineering research. The study built within the subject over the last 20 years has been almost always interested by exploiting the bushy version flexibility to procure the top accuracy. This technique frequently units apart the interpretability of the bought versions. in spite of the fact that, we should always take into account the preliminary philosophy of fuzzy units concept directed to serve the bridge among the human figuring out and the computing device processing. during this problem, the facility of fuzzy types to specific the habit of the true process in a understandable demeanour acquires a superb significance. This booklet collects the works of a gaggle of specialists within the box that suggest the interpretability advancements as a mechanism to procure good balanced fuzzy models.
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Wang. Simplifying fuzzy rule-based models using orthogonal transformation methods. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 29(1):13-24, 1999. 73. J. Yen, L. W. Gillespie. Improving the interpretability of TSK fuzzy models by combining global learning and local learning. IEEE Transactions on Fuzzy Systems, 6(4):530-537, 1998. 74. W. Yu and Z. Bien. Design of fuzzy logic controller with inconsistent rule base. Journal of Intelligent and Fuzzy Systems, 2:147-159,1994.
Chinese Journal of Computers, 24(2):164-172, 2001. 58. R. Silipo and M. Berthold. Discriminative power of input features in a fuzzy model. In D. Hand, J. Kok, and M. Berthold, editors, Advances in Intelligent Data Analysis (IDA-99), volume LNCS 1642, pages 87-98. Springer-Verlag, Heidelberg, Germany, 1999. 59. R. Silipo and M. Berthold. Input features' impact on fuzzy decision processes. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 30(6):821-834, 2000. 60. T. Soderstrom and P.
Functional equivalence guided GA: Thyroid problem, heuristic start, group strategy 35r-------~------~------_r------~------_, 30 20 40 60 GA run number 80 100 Fig. 11. 100 runs for a functional equivalence guided GA (Thyroid group). tion of antecedent conditions may even be explicitly introduced as another optimization objective.