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 study, several artificial neural networks (anns) were developed to estimate seed and grain corn yields in parsabad moghan, iran. the data was collected by a face-to-face interview method from 144 corn farms during 2011. the energy ratios for seed and grain corns were calculated as 0.89 and 2.65, respectively. several multilayer perceptron anns with six neurons in the input layer and one...

computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. nowadays, despite the numerous time series forecasting models propos...

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...

Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...

â  abstract: in this paper, artificial neural network (ann) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. the actual input-output data of the system were measured in order to be used for system identification based on root mean square error (rmse) minimization approach. it was shown that the designed recurrent neural network is able to pr...

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 ...

Economic Dispatch Problem (EDP) has been discussed with reference to the developments based on Artificial Neural Networks (ANN) approaches. A selected survey / overview on Economic Dispatch using Artificial Neural Network within the IEE/IEEE publications frame work have been presented.