نوع مقاله : مقاله پژوهشی
نویسنده
گروه مهندسی معدن، دانشکده مهندسی، دانشگاه کردستان، سنندج، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسنده [English]
The net present value (NPV) index is one of the most important economic parameters in the evaluation of the investment projects. Considering that determining the NPV in most mining projects involves uncertainty, so accurate estimation of this index is a difficult process and need the utilization of suitable methods. In this paper, fuzzy system, neural network and multivariate regression models are used for NPV determination in the Zarshuran gold mine project. Gold price (main product), silver price (byproduct) and discount rate are considered as input parameters to predict NPV in the proposed models. Performance evaluation of the proposed models and comparing their results with the previous studies showed that the accuracy of fuzzy model is somewhat better than the proposed and previous neural network model, and both fuzzy and neural network models are much higher than the statistical model. Also, high determination coefficient and low error of fuzzy and neural network models as well as their good agreements with real data indicate the desired capability of these models in determining the NPV in mining projects. Finally, the sensitivity analysis results of the fuzzy model (accurate proposed model) proved that the gold price and discount rate are the most and least effective parameter on the NPV, respectively. Considering the above results, it can be concluded that the proposed intelligent techniques in this research (especially the fuzzy model) can be used with good reliability in evaluating the mining investment projects in order to cover their involved uncertainty and reduce the investment risk.
کلیدواژهها [English]