In the paper, two pre-processing methods for load forecast sampling data including multiwavelet transformation and chaotic time series are introduced. In addition, multi neural network for load forecast including BP artificial neural network, RBF neural network and wavelet neural network are introduced, too. Then, a combination load forecasting model for power load based on chaotic time series,...

Introduction: A major problem facing the patients with chronic liver diseases is the diagnostic procedure.  The conventional diagnostic method depends mainly on needle biopsy which is an invasive method. There  are  some  approaches  to  develop  a  reliable  noninvasive  method  of  evaluating  histological  changes  in  sonograms. The main characteristic used to distinguish between the normal...

This paper demonstrates classification of PQ events utilizing wavelet transform (WT) energy features by artificial neural network (ANN) and SVM classifiers. The proposed scheme utilizes wavelet based feature extraction to be used for the artificial neural networks in the classification. Six different PQ events are considered in this study. Three types of neural network classifiers such as feed ...

ةـصلاخلا : دقل مدختسا رٌيثآ يف تاجيوملا ة ينقت نيثحا بلا نم فينصت روصلا يف ةجس نلأا ةعجشم جئا تن عم . لعلو بيلاسلأا ر ثآأ ل يلحت يف اً حاجن ةجس نلأا رصتقت نلآا ىتح ليلحت ىلع طقف ةيدامرلا روصلا . يف ةد يدج ة قيرط حرتقنس ف ،ثحبلا اذ ه يف امأ روص نم ةجس نلأا فينصت ة نولم . لا د متعتو ة قيرط ىلع ةيبصعلا تاكبشلاو تاجيوملا مادختسا . وكتت ن ةديدجلا ةقيرطلا نم جارختسا يجيوملا ليلحتلا نم ةصاخ ت...

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...

the record of human brain neural activities, namely electroencephalogram (eeg), is generally known as a non-stationary and nonlinear signal. in many applications, it is useful to divide the eegs into segments within which the signals can be considered stationary. combination of empirical mode decomposition (emd) and hilbert transform, called hilbert-huang transform (hht), is a new and powerful ...

This work describes a voltammetric electronic tongue, in which the quantitative information contained in voltammograms obtained from amperometric sensors is firstly extracted employing the discrete wavelet transform (DWT) and then processed employing artificial neural n i e D i o B ©