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Abstract

Overseas mining investment generally faces considerable risk due to a variety of complex risk factors. Therefore, indexes are often based on conditions of uncertainty and cannot be fully quantified. Guided by set pair analysis (SPA) theory, this study constructs a risk evaluation index system based on an analysis of the risk factors of overseas mining investment and determines the weights of factors using entropy weighting methods. In addition, this study constructs an identity-discrepancycontrary risk assessment model based on the 5-element connection number. Both the certainty and uncertainty of the various risks are treated uniformly in this model and it is possible to mathematically describe and quantitatively express complex system decisions to evaluate projects. Overseas mining investment risk and its changing trends are synthetically evaluated by calculating the adjacent connection number and analyzing the set pair potential. Using an actual overseas mining investment project as an example, the risk of overseas mining investment can be separated into five categories according to the risk field, and then the evaluation model is quantified and specific risk assessment results are obtained. Compared to the field investigation, the practicability and effectiveness of the evaluation method are illustrated. This new model combines static and dynamic factors and qualitative and quantitative information, which improves the reliability and accuracy of risk evaluation. Furthermore, this evaluation method can also be applied to other similar evaluations and has a certain scalability.

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Authors and Affiliations

Zhaoyang Ma
Guoqing Li
Nailian Hu
Di Liu
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Abstract

The mean-reversion model is introduced into the study of mineral product price prediction. The gold price data from January 2018 to December 2021 are selected, and a mean-reverting stochastic process simulation of the gold price was carried out using Monte Carlo simulation (MCS) method. By comparing the statistical results and trend curves of the mean-reversion (MR) model, geometric Brownian motion (GBM) model, time series model and actual price, it is proved that the mean-reversion process is valid in describing the price fluctuation of mineral product. At the same time, by comparing with the traditional prediction methods, the mean-reversion model can quantitatively assess the uncertainty of the predicted price through a set of equal probability stochastic simulation results, so as to provide data support and decision-making basis for the risk analysis of future economy.
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Authors and Affiliations

Shuwei Huang
1 2 3
ORCID: ORCID
Zhaoyang Ma
1
Feng Jin
1
ORCID: ORCID
Yuansheng Zhang
1

  1. BGRIMM Technology Group, China
  2. Beijing Key Laboratory of Nonferrous Intelligent Mining Technology, China
  3. BGRIMM Intelligent Technology Co. Ltd, China
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Abstract

This paper researches the application of grey system theory in cost forecasting of the coal mine. The grey model (GM(1.1)) is widely used in forecasting in business and industrial systems with advantages of minimal data, a short time and little fluctuation. Also, the model fits exponentially with increasing data more precisely than other prediction techniques. However, the traditional GM(1.1) model suffers from the poor anti-interference ability. Aimed at the flaws of the conventional GM(1.1) model, this paper proposes a novel dynamic forecasting model with the theory of background value optimization and Fourier-series residual error correction based on the traditional GM(1.1) model. The new model applies the golden segmentation optimization method to optimize the background value and Fourier-series theory to extract periodic information in the grey forecasting model for correcting the residual error. In the proposed dynamic model, the newest data is gradually added while the oldest is removed from the original data sequence. To test the new model’s forecasting performance, it was applied to the prediction of unit costs in coal mining, and the results show that the prediction accuracy is improved compared with other grey forecasting models. The new model gives a MAPE & C value of 0.14% and 0.02, respectively, compared to 1.75% and 0.37 respectively for the traditional GM(1.1) model. Thus, the new GM(1.1) model proposed in this paper, with advantages of practical application and high accuracy, provides a new method for cost forecasting in coal mining, and then help decision makers to make more scientific decisions for the mining operation.

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Authors and Affiliations

Di Liu
Guoqing Li
Emmanuel K. Chanda
Nailian Hu
Zhaoyang Ma
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Abstract

One of the most critical aspects of mine design is to determine the optimum cut-off grade. Despite Lane’s theory, which aims to optimize the cut-off grade by maximizing the net present value (NPV), which is now an accepted principle used in open pit planning studies, it is less developed and applied in optimizing the cut-off grade for underground polymetallic mines than open pit mines, as optimization in underground polymetallic mines is more difficult. Since there is a similar potential for optimization between open pit mines and underground mines, this paper extends the utilization of Lane’s theory and proposes an optimization model of the cut-off grade applied to combined mining-mineral processing in underground mines with multi-metals. With the help of 3D visualization model of deposits and using the equivalent factors, the objective function is expressed as one variable function of the cut-off grade. Then, the curves of increment in present value versus the cut-off grade concerning different constraints of production capacities are constructed respectively, and the reasonable cut-off grade corresponding to each constraint is calculated by using the golden section search method. The defined criterion for the global optimization of the cut-off grade is determined by maximizing the overall marginal economics. An underground polymetallic copper deposit in Tibet is taken as an example to validate the proposed model in the case study. The results show that the overall optimum equivalent cut-off grade, 0.28%, improves NPV by RMB 170.2 million in comparison with the cut-off grade policy currently used. Thus, the application of the optimization model is conducive to achieving more satisfactory economic benefits under the premise of the rational utilization of mineral resources.

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Authors and Affiliations

Di Liu
Guoqing Li
Nailian Hu
Guolin Xiu
Zhaoyang Ma
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Abstract

At present, with the increase of production capacity and the promotion of production, the reserves

of most mining enterprises under the original industrial indexes are rapidly consumed, and the full

use of low-grade resources is getting more and more attention. If mining enterprises want to make

full use of low-grade resources simultaneously and obtain good economic benefits to strengthening

the analysis and management of costs is necessary. For metal underground mines, with the gradual

implementation of exploration and mining projects, capital investment and labor consumption are

dynamic and increase cumulatively in stages. Consequently, in the evaluation of ore value, we should

proceed from a series of processes such as: exploration, mining, processing and the smelting of

geological resources, and then study the resources increment in different stages of production and the

processing. To achieve a phased assessment of the ore value and fine evaluation of the cost, based on

the value chain theory and referring to the modeling method of computer integrated manufacturing

open system architecture (CIMOSA), the analysis framework of gold mining enterprise value chain is

established based on the value chain theory from the three dimensions of value-added activities, value

subjects and value carriers. A value chain model using ore flow as the carrying body is built based on

Petri nets. With the CPN Tools emulation tool, the cycle simulation of the model is carry out by the

colored Petri nets, which contain a hierarchical structure. Taking a large-scale gold mining enterprise

as an example, the value chain model is quantified to simulate the ore value formation, flow, transmission

and implementation process. By analyzing the results of the simulation, the ore value at different

production stages is evaluated dynamically, and the cost is similarly analyzed in stages, which can improve mining enterprise cost management, promote the application of computer modeling and

simulation technology in mine engineering, more accurately evaluate the economic feasibility of ore

utilization, and provide the basis for the value evaluation and effective utilization of low-grade ores.

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Authors and Affiliations

Zhaoyang Ma
Nailian Hu
Guoqing Li
Di Liu
Tao Pan

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