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Journal of Mining and Environment، جلد ۶، شماره ۱، صفحات ۲۱-۳۰
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عنوان انگلیسی Application of artificial neural network and genetic algorithm to modelling the groundwater inflow to an advancing open pit mine
چکیده انگلیسی مقاله In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (HH) in the observation wells to the distance of observation wells from the centre of pit were used as inputs to the network. An ANN-GA with 4-5-3-1 arrangement was found capable to predict the groundwater inflow to mine pit. The accuracy and reliability of model was verified by field data. Predicted results were very close to the field data. The correlation coefficient (R) value was 0.998 for training set, and in testing stage it was 0.99.
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نویسندگان مقاله s بهرامی |
school of mining engineering, college of engineering, university of tehran, tehran, iran
سازمان اصلی تایید شده: دانشگاه تهران (Tehran university)

f دولتی ardejani | doulati ardejani
mine environment and hydrogeology research laboratory, university of tehran, tehran, iran
سازمان اصلی تایید شده: دانشگاه تهران (Tehran university)

نشانی اینترنتی http://jme.shahroodut.ac.ir/article_330_a080189c28efb629c5ee4cd88aec714d.pdf
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