The application of conjunctive aggregation operators in fuzzy control systems with 2 inputs is discussed and the effect of the choice of a continuous t-norm operator in inference phase for TSK systems is computed. It is shown that the choice of a continuous t-norm modelling AND connective in antecedent part of fuzzy rules can be reduced just to strict or nilpotent t-norm. Moreover, it is shown ...

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple ov...

One of the best examples of mathematically rigorous signal processing in finance is the Black-Scholes model for price evolution of financial options. To address the same problem, this paper proposes a Takagi-SugenoKang (TSK) fuzzy rule-based option pricing model that requires only a small number of rules to describe highly complex financial signals such as option prices. The findings for this d...

The conventional procedure for the purification of the high affinity K+ uptake ATPase (KdpABC) from Escherichia coli involves a tedious three-column protocol (final enzyme purity, approximately 90%; activity yield, 6.5% (Siebers, A., and Altendorf, K. (1988) Eur. J. Biochem. 178, 131-140)). We have now developed a highly effective one-column (Fractogel TSK AF-Red) protocol yielding an enzyme pr...

This paper presents the application of nonlinear channel equalizers, based on fuzzy IF-THEN rules, for Global System for Mobile (GSM) communication applications. Two types of fuzzy filters namely Type–1 TSK (Takagi – Sugeno – Kang) fuzzy adaptive filter (FAF) and Type–2 TSK FAF are considered for performance comparison. The equalizers proposed can be trained with very short training signal of 2...

Several methodologies for function approximation using TSK systems make use of clustering techniques to place the rules in the input space. Nevertheless classical clustering algorithms are more related to unsupervised learning and thus the output of the training data is not taken into account or, simply the characteristics of the function approximation problem are not considered. In this paper ...

This paper presents a new method to control of robot manipulator in task space. In the proposed control method, a combination of feedback linearization, sliding mode control and first-order TSK fuzzy system has been utilized. In this method, the bounds of structural and non-structural uncertainties by using feedback linearization method are reduced and to overcome the remaining uncertainties, s...

An attempt was made to substantiate a modori (thermal gel degradation) inducing effect of a latent serine proteinase. The proteinase was purified homogeneously from the sarcoplasmic fraction of threadfin bream muscle using a combination of DEAF-cellulose, Con A-Sepharose, ArgSepharose, Shim-pack HAC, and TSK-gel G3000SWXL column chromatographies. Its molecular weight was estimated as 77,000 by ...

This paper proposes a novel adaptive group organization cooperative evolutionary algorithm (AGOCEA) for TSK-type neural fuzzy networks design. The proposed AGOCEA uses group-based cooperative evolutionary algorithm and selforganizing technique to automatically design neural fuzzy networks. The group-based evolutionary divided populations to several groups and each group can evolve itself. In th...