Rahim Mortezaie; Seyed Davoud Mohammadi; Vahab Sarfarazi
Abstract
One of the most important tasks in conducting a laboratory research work is how to make the samples. The purpose of this research work is to create heterogeneous rock-like samples containing non-persistent notches. Regarding that, the molds with dimensions of 250 mm x 200 mm x 50 mm are made. A mixture ...
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One of the most important tasks in conducting a laboratory research work is how to make the samples. The purpose of this research work is to create heterogeneous rock-like samples containing non-persistent notches. Regarding that, the molds with dimensions of 250 mm x 200 mm x 50 mm are made. A mixture of plaster and water with different mixing percentages is used to make the heterogeneous samples. Various techniques are also employed to create non-persistent notches on the samples. One of the methods to create a notch is to insert an aluminum blade into the groove of the mold, and finally, remove it after the plaster slurry has hardened. Due to the displacement of the blade and its tilting during slurring, the notches are out of the vertical position. In addition to the mentioned method, other methods such as water jet, cutting by thread, cutting by diamond wire cutting, cutting by rotary saw, and using hand saw are applied. Finally, using a hand saw to create a notch on the samples is chosen as the best method.
Sirvan Moradi; Seyed Davoud Mohammadi; Abbas Aghajani Bazzazi; Ali Aali Anvari; Ava Osmanpour
Abstract
Feasibility studies of mining and industrial investment projects are usually associated with uncertain parameters; hence, these investigations rely on prediction. In these particular conditions, simulation and modelling techniques remain the most significant approaches to reduce the decision risk. Since ...
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Feasibility studies of mining and industrial investment projects are usually associated with uncertain parameters; hence, these investigations rely on prediction. In these particular conditions, simulation and modelling techniques remain the most significant approaches to reduce the decision risk. Since several uncertain parameters are incorporated in the modelling process, distribution functions are employed to explain the parameters. However, due to the usual constrain of limited data, these functions cannot significantly explain the variation of those uncertain parameters. Support vector machine, one of the efficient techniques of artificial intelligence, provides the appropriate results in the classification and regression tasks. The principal aims of this research work are to integrate the simulation and artificial intelligence methods to manage the risk prediction of an economic system under uncertain conditions. The financial process of the Halichal mine in the Mazandaran province, Iran, is considered a case study to prove the performance of the support vector machine technique. The results show that integrating the simulation and support vector machine techniques can provide more realistic results, especially when including uncertain parameters. The correlation between the net present value obtained from the simulation and the net present value is about 0.96, which shows the capability of artificial intelligence methods and the simulation process. The root mean square error of the support vector machine prediction is about 0.322, which indicates a low error rate in the net present value estimation. The values of these errors prove that this method has a high accuracy and performance for predicting a net present value in the Halichal granite mine.