Identification and classification ofvoltage and current disturbances in power systems is an important task in power system monitoring and protection. Most power quality disturbances are non-stationary and transitory and the detection and classification have proved to be very demanding. New intelligent system technologies using wavelet transform, expert systems and artificial neural networks pro...

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

The hybrid fuzzy differential equations have a wide range of applications in science and engineering. We consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. Here neural network is considered as a part of large eld called neural computing or soft computing. The proposed algorithm is illustrated by numerical examples and the result...

Retrieval of images based on low level visual features such as color, texture and shape have proven to have its own set of limitations under different conditions. As the number and size of image databases grows, accurate and efficient content-based image retrieval systems become increasingly important in business and in the everyday lives of people around the world. In this paper we describe a ...

Abstract: In this paper an outliers resistant learning algorithm for the radial-basis-fuzzy-wavelet-neural network based on R. Welsh criterion is proposed. Suggested learning algorithm under consideration allows the signals processing in presence of significant noise level and outliers. The robust learning algorithm efficiency is investigated and confirmed by the number of experiments including...

This paper highlights on the techniques used in the HVDC transmission line protection for the faults occurring at various locations. The different techniques deployed for HVDC protection includes Distance Protection technique, Discrete Fourier Transform technique, Artificial Neural Network technique, Fuzzy logic technique, Wavelet Transform technique, Natural Frequency technique, Independent co...

Temperature and humidity are two highly coupled variables in a control system, which need to be decoupled for effective control. Moreover, the coupling problem may get more severe and the two control loops may produce a strong interference to each other that can cause system instability when the humidity is measured by dry-and-wet bulb method. In this study, a control method based on fuzzy-neur...

Fuzzy neural networks have been successfully applied to generate predictive rules for stocks forecasting. This paper presents a methodology for forecasting S&P 500 index based on the neural network with weighted fuzzy membership functions (NEWFM) and time series of S&P 500 index based on the defuzzyfication of weighted average method (The fuzzy model suggested by Takagi and Sugeno in 1985). NEW...

In this paper we have studied the application on the fuzzy-hybrid neural network for electrocardiogram (ECG) beat classification. Instead of original ECG beat, we have used; autoregressive model coefficients, higher-order cumulant and wavelet transform variances as features. Tested with MIT/BIH arrhytmia database, we observe significant performance enhancement using proposed method. 2004 Elsevi...

The training algorithm of Wavelet Neural Networks (WNN) is a bottleneck which impacts on the accuracy of the final WNN model. Several methods have been proposed for training the WNNs. From the perspective of our research, most of these algorithms are iterative and need to adjust all the parameters of WNN. This paper proposes a one-step learning method which changes the weights between hidden la...