The ability of Artificial Neural Network (ANN) for estimating the natural gas demand load for the next day and month of the populated cities has shown to be a real  concern. As the most applicable network, the ANN with multi-layer back propagation perceptrons is used to approximate functions. Throughout the current work, the daily effective temperature is determined, and then the weather data w...

Suspended particles have deleterious effects on human health and one of the reasons why Tehran is effected is its geographically location of air pollution. One of the most important ways to reduce air pollution is to predict the concentration of pollutants. This paper proposed a hybrid method to predict the air pollution in Tehran based on particulate matter less than 10 microns (PM10), and the...

In this work, classification of spirometric pulmonary function test data performed using two artificial neural network methods is compared and reported. The pulmonary function data (N=150) were obtained from volunteers, using commercially available Spirometer, and recorded by standard data acquisition protocol. The data were then used to train (N=100) as well as to test (N=50) the neural networ...

A Back Propagation Artificial Neural Network (BPANN) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. In this study, 261 GPS/Leveling and 8869 gravity intensityvalues of Iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“BPANN”, and “collocation” ...

The purpose of this study is to evaluate the performance analysis of multilayer feed forward neural networks trained with back propagation algorithm & descent gradient Radial basis function network for the pattern classification of hand written curve script. This analysis has been done for handwritten text of three letters and for the individual English vowels. This analysis in the performance ...