The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorith...

Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...

Artificial neural networks (ANNs) are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the capability of ANN in predicting body behavior in pain-producing situations is evaluated. A three-layer back-propagation ANN is designed using MATLAB software. The inputs include the magnitude of stimulation in pain fibers, touch fibers and cen...

The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...

The artificial neural networks (ANN) are the learning algorithms and mathematical models, which mimic the information processing ability of human brain and can be used to non linear and complex data. The aim of this study was to compare artificial neural network and regression models for prediction of body weight in Raini Cashmere goat. The data of 1389 goats for body weight, height at withers ...

improving time series forecastingaccuracy is an important yet often difficult task.both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. in this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

in the present study iran’s rice imports trend is forecasted, using artificial neural networks and econometric methods, during 2009 to 2013, and their results are compared. the results showed that feet forward neural network leading with less forecast error and had better performance in comparison to econometric techniques and also, other methods of neural networks, such as recurrent networks a...