Structure identification of fuzzy model
Fuzzy Sets and Systems
A unified approach to define fuzzy integrals
Fuzzy Sets and Systems
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Some quantities represented by the Choquet integral
Fuzzy Sets and Systems
Monotone set functions defined by Choquet integral
Fuzzy Sets and Systems
Fuzzy engineering
Numerical methods for calculating the fuzzy integral
Fuzzy Sets and Systems
The nature of mathematical modeling
The nature of mathematical modeling
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Parameter determination for a generalized fuzzy model
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Comments on “Choquet fuzzy integral-based hierarchical networks for decision analysis” [and reply]
IEEE Transactions on Fuzzy Systems
Structure identification of generalized adaptive neuro-fuzzy inference systems
IEEE Transactions on Fuzzy Systems
From a Gaussian mixture model to additive fuzzy systems
IEEE Transactions on Fuzzy Systems
From a Gaussian Mixture Model to Nonadditive Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems
Generalization of adaptive neuro-fuzzy inference systems
IEEE Transactions on Neural Networks
Estimation of fuzzy measures using covariance matrices in Gaussian mixtures
Applied Computational Intelligence and Soft Computing
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An adaptive non-additive generalized fuzzy model (GFM) is presented in this paper using the framework of Gaussian mixture model (GMM) which provides the membership functions for the input fuzzy sets. By replacing the consequent part of the additive GFM rule by a non-additive function, we obtain the non-additive GFM. The coefficients of the non-additive function then become the fuzzy measures. The defuzzified output constructed from both the premise and consequent parts of the modified GFM rules in the wake of non-additiveness takes the form of Choquet fuzzy integral. The parameters of the premise and the consequent parts of the non-additive fuzzy rules are updated based on the estimation error on the arrival of each online data to make the system adaptive. The resulting adaptive non-additive fuzzy model is applied on two benchmark applications and the results demonstrate the advantage of the adaptive feature.