The parameter conditions are developed for both single-input and multi-input TSK fuzzy systems where the involved fuzzy membership functions are differentiable everywhere or bar some finite points. The derived monotonicity conditions consist of two parts: the conditions on the consequent parts and the ...
We propose reinforcement learning (RL) with Takagi-Sugeno-Kang (TSK) fuzzy systems and highlight the value of exploring the intersection of RL and fuzzy logic in producing explainable systems.
Keywords:Imagefusion;Supervisedlearning;TakagiSugenoKang(TSK)fuzzysystem 1 引言 图像融合【 1是通过一种特定算法将两幅或多幅 图像合成为一幅新图像的过程。近年来,在已有的 图像融合方法中又以神经网络图像融合领域的成果 较丰富,其可进一步分为脉冲耦合神经网络图像融 ...
Abstract:Ensemble learning is one of the most popular methods for nonlinear systems.However,when the tradi-tional ensemble models of TSK fuzzy classifiers are directly applied to imbalanced data,their learning performances will be deteriorated with poor generalization ability.In order to tackle with this...
A rule base covering the entire input domain is required for the conventional Mamdani inference and Takagi–Sugeno–Kang (TSK) inference. Fuzzy i
TSKThe Sleuth Kit(UNIX) TSKThe Silent Killer(gaming clan) TSKTesked(Swedish: teaspoon) TSKTall Skinny Kiwi TSKThe Subtle Knife(Phillip Pullman book) TSKSkin Temperature TSKTurk Silahli Kuvvetleri(Turkish Armed Forces) TSKTakagi-Sugeno-Kang(fuzzy network model) ...
Interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy neural networkCombined modelFor the purpose of environmental protection and economic development, photovoltaic (PV) power generation is becoming increasingly popular, but the intermittence and uncertainty in PV power generation make grid-connected PV ...
This paper suggests a synergy of fuzzy logic and nature-inspired optimization in terms of the nature-inspired optimal tuning of the input membership functions of a class of Takagi-Sugeno-Kang (TSK) fuzzy models dedicated to Anti-lock Braking Systems (ABSs). A set of TSK fuzzy models is ...
Typical FS models include the Takagi-Sugeno-Kang (TSK) FS [3], the Mamdani-Larsen (ML) FS [4], the generalized FS (GFS) [5] and others, among which TSK FSs are the most investigated models due to their high efficiency. To date, many TSK FS construction methods have been developed,...
TSK fuzzy systemsdynamic rule weightsstacked structureoutlier detectionFuzzy rules are very important in Takagi-Sugeno-Kang (TSK) fuzzy systems as they not only provide a mapping mechanism for input patterns but also make fuzzy systems interpretable. Current works further introduce rule weights to ...