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The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC neural networks are the supervised neural networkswhich use the fuzzified versions of Learning Vector Quantization (LVQ). In this paper,several important adaptive learning algorithms are compared from the viewpoint of structure andlearning rule. The performances of several adaptive learning algorithms are compared usingIris data set.

In this paper, a pointwise pseudo-metric function on the L-realline is constructed. It is proved that the topology induced by this pointwisepseudo-metric is the usual topology.

In this paper, we deal with fuzzy random variables for inputs andoutputs in Data Envelopment Analysis (DEA). These variables are considered as fuzzyrandom flat LR numbers with known distribution. The problem is to find a method forconverting the imprecise chance-constrained DEA model into a crisp one. This can bedone by first, defuzzification of imprecise probability by constructing a suitablemembership function, second, defuzzification of the parameters using an α-cut andfinally, converting the chance-constrained DEA into a crisp model using the methodof Cooper [4].

A theorem was recently introduced to establish a relationship betweengoal programming and fuzzy programming for vectormaximum problems.In this short note it is shown that the relationship does not exist underall circumstances. The necessary correction is proposed.

In this paper we present a method for solving fuzzy linear systemsby two crisp linear systems. Also necessary and sufficient conditions for existenceof solution are given. Some numerical examples illustrate the efficiencyof the method.

This paper presents the application of the fuzzy-neuro method toinvestigate transformer inrush current. Recently, the frequency environment ofpower systems has been made more complicated and the magnitude of the secondharmonic in inrush current has been decreased because of the improvement of caststeel. Therefore, traditional approaches will likely mal-operate in the case ofmagnetizing inrush with low second component and internal faults with highsecond harmonic. The proposed scheme enhances the inrush detection sensitivity ofconventional techniques by using a fuzzy-neuro approach. Details of the designprocedure and the results of performance studies with the proposed detector aregiven in the paper. The results of performance studies show that the proposedalgorithm is fast and accurate.

The present article discusses and presents a new and comprehensive approachaimed at measuring the maturity and quality of software processes. This method has beendesigned on the basis of the Software Capability Maturity Model (SW-CMM) and theMulti-level Fuzzy Inference Model and is used as a measurement and analysis tool. Among themost important characteristics of this method one can mention simple usage, accuracy,quantitative measures and comparability. Fuzzy logic-based tools are designed to providesuch functions.

In this paper, we apply the Biswas’ idea of anti fuzzy subgroups toideals of near-rings. We introduce the notion of anti fuzzy ideals of near-rings,and investigate some related properties.

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