A local linear wavelet neural network (LLWNN) is presented in this paper. The difference of the network with conventional wavelet neural network (WNN) is that the connection weights between the hidden layer and output layer of conventional WNN are replaced by a local linear model. A hybrid training algorithm of particle swarm optimization (PSO) with diversity learning and gradient descent metho...

The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

in today’s business competitive world, decision makers of companies try to employ standard, efficient, theoretical and operational proven methods as a competitive advantage for making their critical strategic business decisions in order to survive in their industry. in this paper, a hybrid model based on fuzzy analytic hierarchy process (fahp) and artificial neural network (ann) is presented. t...

Forecasting financial markets is an important issue in finance area and research studies. On one hand, the importance of prediction, and on the other hand, its complexity, have led to huge number of researches which have proposed many forecasting methods in this area. In this study, we propose a hybrid model including Wavelet Transform, ARMA-GARCH and Artificial Neural Network (ANN) for single-...

abstract background: a computer aided diagnosis system was established using the wavelet transform and neural network to differentiate malignant from benign in a   group of patients with histo-pathologically proved breast lesions based on the data derived independ­ently from time-intensity profile.   materials and methods: the per­formance of the artificial neural network (ann) was evaluated us...

The crude oil prices as well as the effective exchange rate of the dollar are both time series and non -stationary as well. In this paper, we investigate the relationship between real effective exchange rate and crude oil prices by hybrid wavelet network. We use a simple Multi-layer Perceptron Neural Network (MLPNN) based wavelet decomposition to analyse the relatio nship between real effective...

in this study the wavelet neural network (wnn) and artificial neural network (ann) were used to simulate barley breakage percentage in combine harvester. the models have been trained using the same data conditions. air temperature, thresher cylinder speed, distance between thresher cylinder and concave (back and forth) and the percentage of barely moisture were as the input variables. the resul...

In this study, hybrid Particle Swarm Optimization (PSO)-based Wavelet Neural Network (WNN) for natural scene text extraction is presented. In our approach, wavelet transformation is done on the different current and the wavelet coefficients are obtained. The wavelet coefficients are given as inputs to the wavelet neural network trained by Particle Swarm Optimization (PSO-WNN). The final network...