In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...

In this study, a neural network based methodology is proposed for power transmission line faults. The proposed method uses Probabilistic Neural Network (PNN) for classifying fault types and Resilient Propagation algorithm (RPROP) for detecting fault locations. Wavelet Transform is also proposed for feature selection and analysis. The hybrid system proposed in this study is tested using a simula...

as the t-wave section in electrocardiogram (ecg) illustrates the repolarisation phase of heart activity, the information which is accumulated in this section is so significant that can explain the proper operation of electrical activities in heart. long qt syndrome (lqt) and t-wave alternans (twa) have imperceptible effects on time and amplitude of t-wave interval. therefore, t-wave shapes of t...

Curve and surface thinning are widely-used skeletonization techniques for modeling objects in 3 dimensions. In the case of disordered porous media analysis, however, neither is really efficient since the internal geometry of the object is usually composed of both rod and plate shapes. This paper concludes an application of discrete wavelet transform (WT) and complex wavelet transform (CWT) in i...

in this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. utilizing the generalized characterization theorem. then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. here neural network is considered as a part of large eld called n...

accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. combined wavelet-artificial neural network (wann) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. this study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...

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...