A novel fuzzy-neural tree (FNT) is presented, where each tree node uses a Gaussian as a fuzzy membership or possibility distribution in place of sigmoidal function in conventional neural networks. Although neural networks with Gaussian activation functions as well as different types of cooperative neuro-fuzzy systems have been extensively described in the literature, the FNT presented in this p...

This paper provides an overview to detect, locate, and characterize fault in structural and mechanical systems using various methods. Since last few decades experimentally measured frequencies has been extensively used to crack detection. The relationships between frequency changes and structural damage are discussed. Various reverse techniques proposed for detecting fault using natural frequen...

This paper describes the design and development of a novel controller for a non-linear power electronic converter. Neuro-Fuzzy controller is proposed to improve the performance of the buck &boost converters. The duty cycle of the buck & boost converters are controlled by NeuroFuzzy controller. The conventional PI controllers for such converters, designed under the worst case condition of maximu...

In this paper, an adaptive neuro fuzzy interference (ANFIS) based hybrid field oriented speed controlling of an induction motor is proposed. The proposed hybrid field oriented speed controller results attractive performance of induction motor with the potential features of both Artificial Neural network (ANN) and Fuzzy Logic Controller (FLC). In this topology the Artificial Neural Network (ANN)...

Traditional air quality assessment is realized using air quality indices which are determined as mean values of selected air pollutants. Thus, air quality assessment depends on strictly given limits without taking into account specific local conditions and synergic relations between air pollutants and other meteorological factors. The stated limitations can be eliminated, e.g. using systems bas...

The paper introduces an early-warning method using multiple financial crises indicators which outputs relevant alerts compared to a precise indication of crisis inception, serving as an effective tool for decision makers. By leveraging fuzzy logic techniques, we design a multi-level fuzzy decision support system based on the evolution of credit growth, housing prices and GDP gap. A neuro-fuzzy ...

As a result from the demanding of process safety, reliability and environmental constraints, a called of fault detection and diagnosis system become more and more important. This statement can be seen from literature covering different aspects and applications implementation. A variety of methods already proposed whether applied single or combined method. One of the feasible ways is by combinin...

Neural and traditional techniques have been compared for the particular task of automatic ECG analysis. A large validated ECG database has been used. Statistical methods, neural architectures with supervised and unsupervised learning, and a neuro-fuzzy architecture have been considered. The results from the connectionist approach are always at least comparable with those coming from more tradit...

The automatic selection and composition of Web services rely strongly on the manner to deal with ambiguity inherent to the description of functionalities of these services and the client’s requests. Quality of Service (QoS) criteria become crucial in Web services selection and the problem of checking that a web service satisfies a given level of QOS is considered in recent research works. This ...