This study developed a new perspective of artificial neural networks using dimensional analysis to be applicable to certain prediction problems. To this end, dimensional analysis was combined with multi-layer perceptron and radial basis function neural networks for application to prediction of blast-induced dust emission. The dimensional analysis concept was designed to improve the prediction performance in the neural network process. The results of the developed neural networks were validated by comparing them with the measured results. Insights indicated that the dimensional multi-layer perceptron neural network analysis was better than that of the dimensional radial basis function neural network. In addition, the region’s winds and their impacts on dust emissions were investigated in detail to estimate wind velocity and direction. A radius of approximately 1 km was identified as the dust impact zone, where agricultural and residential areas may be affected adversely.
کلید واژگان :Dust emission, Air pollution, Bench blasting, Dimensional analysis, Multi-layer artificial neural network
ارزش ریالی : 600000 ریال
با پرداخت الکترونیک