Prediction of Rock Fragmentation Due to Blasting in Sarcheshmeh Copper Mine Using Artificial Neural Networks |
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Authors: | M Monjezi H Amiri A Farrokhi K Goshtasbi |
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Institution: | (1) Tarbiat Modares University, Tehran, Iran;(2) Islamic Azad University-Tehran South Branch, Tehran, Iran |
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Abstract: | The main objective in production blasting is to achieve a proper fragmentation. In this paper, rock fragmentation the Sarcheshmeh
copper mine has been predicted by developing a model using artificial neural network. To construct the model, parameters such
as burden to spacing ratio, hole-diameter, stemming, total charge-per-delay and point load index have been considered as input
parameters. A model with architecture 9-8-5-1 trained by back propagation method was found to be optimum. To compare performance
of the neural network, statistical method was also applied. Determination coefficient (R
2) and root mean square error were calculated for both the models, which show absolute superiority of neural network over traditional
statistical method. |
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Keywords: | |
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