引用本文:李守军,马小平,杨春雨.基于模糊区间值GM(1, 1)预测模型及几何布朗运动 的矿山投资决策[J].控制理论与应用,2019,36(4):636~650.[点击复制]
LI Shou-jun,MA Xiao-ping,YANG Chun-yu.Decision making of mine investment based on fuzzy interval-valued GM(1, 1) model and geometric Brown motion[J].Control Theory and Technology,2019,36(4):636~650.[点击复制]
基于模糊区间值GM(1, 1)预测模型及几何布朗运动 的矿山投资决策
Decision making of mine investment based on fuzzy interval-valued GM(1, 1) model and geometric Brown motion
摘要点击 1964  全文点击 893  投稿时间:2017-11-16  修订日期:2018-05-09
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DOI编号  10.7641/CTA.2018.70835
  2019,36(4):636-650
中文关键词  模糊区间  GM(1,1)  几何布朗运动  矿山投资  评估决策
英文关键词  Fuzzy interval-valued theory  GM (1,1) model  Geometric Brown motion  Mine investment  Evaluation decision making
基金项目  国家自然科学基金(61374043, 61603392)
作者单位E-mail
李守军* 中国矿业大学 lishoujunbox@126.com 
马小平 中国矿业大学  
杨春雨 中国矿业大学  
中文摘要
      提出一种新的投资决策方法并应用到矿山投资实践中去是本文的研究核心. 该方法以净现值为目标函数, 以价格预测及成本评估为中心, 综合应用了模糊区间数灰色预测方法和几何布朗运动随机过程理论. 首先, 给出了模糊数到区间灰数的转换方法, 然后, 采用对区间序列上下限分别预测的思路建立了模糊区间数灰色预测模型, 并给出了模型精度的检验标准. 接着, 通过路径矩阵、组合实验、可视化比较及人工分析的方法得到了合理的布朗运动系数值完成了成本预测. 最后, 结合一个铜矿投资项目, 分别应用所提出的模糊区间灰色模型及几何布朗运动理论对价格和成本进行了预测和模拟, 成功地实现了金属矿山风险投资的评估并形成了可行性的决策参考.
英文摘要
      The core of this paper is to put forward a new method of investment decision-making and apply it to the practice of mine investment. Taking the net present value as the objective function and the prediction of price and cost as the center, the method has combined the fuzzy interval grey prediction method with the geometric Brown motion stochastic process together. The transformation method of fuzzy number to interval grey number is given firstly. Then, the grey interval prediction model is established based on the idea of forecasting the upper and lower limits of interval sequence respectively. To obtain operating cost, key Brownian motion coefficients are obtained by path matrix, combination experiment, visual comparison and manual analysis. Finally, through a copper investment project, the proposed method based on fuzzy interval GM(1,1) prediction model and Brownian motion stochastic process theory is used to predict the metal price and operating costs successfully. As a result, risk assessment of metal mine is realized and feasible decision-making is formed.