In this article, firstly the factors influencing the prices of cash market transactions on the basis of gold coin (Bahar Azadi coin) prices and futures contract trading on the Iran Mercantile Exchange are examined during a full year. Then, based on these factors, two new models for predicting the price of the futures contract of gold coin have been presented. These patterns are based on the general linear regression model in a vague and Z-based environment. To this end, regression estimation by the neural network with Z-number-based coefficients and D distance-based optimization technique and the Z-numbering method are used. We also compare some of the proposed methods in terms of efficiency with our previous method (which is the only method available to estimate regression coefficients). We show that the proposed method in this paper has less accuracy and less computational cost. It shows that the new proposed method has better accuracy and less computational cost. Finally, in two practical examples the price of forthcoming coins is anticipated.

在本文中，首先在整个一年中研究了影响基于金币（Bahar Azadi币）价格和伊朗商品交易所上的期货合约交易的现金市场交易价格的因素。然后，基于这些因素，提出了两种新的金币期货合约价格预测模型。这些模式基于模糊和基于Z的环境中的一般线性回归模型。为此，使用基于Z数的系数和基于D距离的优化技术以及Z使用编号方法。我们还将效率方面的一些建议方法与我们以前的方法（这是唯一可用于估计回归系数的方法）进行比较。我们表明，本文提出的方法具有较低的准确性和较少的计算成本。结果表明，该方法具有较高的精度和较低的计算量。最后，在两个实际的例子中，预期即将到来的硬币的价格。