Introduction: Epilepsy is a clinical syndrome in which seizures have a tendency to recur. Sodium valproate is the most effective drug in the treatment of all types of generalized seizures. Finding the optimal dosage (the lowest effective dose) of sodium valproate is a real challenge to all neurologists. In this study, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) was pre...

A multi objective Honey Bee Mating Optimization (HBMO) designed by online learning mechanism is proposed in this paper to optimize the double Fuzzy-Lead-Lag (FLL) stabilizer parameters in order to improve low-frequency oscillations in a multi machine power system. The proposed double FLL stabilizer consists of a low pass filter and two fuzzy logic controllers whose parameters can be set by the ...

An adaptive watermarking method based on the human visual system model and the fuzzy inference system in wavelet domain is proposed. Fuzzy logic is used for data fusion and builds a HVS model for spatial masking in wavelet domain. Modeling spatial masking is a complicated task and there is no single theoretical formulation to precisely compute the perceptual value for a corresponding wavelet co...

this paper introduces an indirect adaptive fuzzy sliding mode controller as a power system stabilizer for damping local and inter-area modes of oscillations of multi-machine power systems. this controller is designed based on the combination of sliding mode controller and the fuzzy logic systems. the fuzzy systems are used to approximate the unknown functions of power system model. generator sp...

The paper deals with an idea of a linguistic knowledge representation and a linguistic inference. Relational linguistic fuzzy model with weights of rules is utilising. The probability of linguistic values of antecedent and consequent variables, calculated according to Zadeh’s definition, is proposed to formulate a linguistic fuzzy model of a stochastic system. The linguistic inference procedure...

In this paper, we present an evolutionary multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler, more compact and still accurate linguistic fuzzy models by learning fuzzy inference operators together with Rule Base. The Multiobjective Evolutionary Algorithm proposed generates a set of Fuzzy Rule Based Systems with diff...

We present a new novel method of automatically generating a multi-variable fuzzy inference system from given sample sets. We rst decompose the sample set, say , into a cluster of sample sets associated with the given input variables, then compute the associated fuzzy rules and membership functions for each variable, independent of the other variables, by solving a single input multiple outputs ...

The application of rail buckling models is often limited by uncertain information with respect to track properties, and many conventional are poorly suited network-wide or even regional application. Here, a methodology using fuzzy sets presented that, when trained data can use inputs properties predict the minimum temperature increase for particular track. An investigation impact size training ...