基于多基因遗传规划的矿石品位估计

摘要 由于矿床形成过程复杂、控制因素多，导致估计矿石品位相对困难.尽量降低矿床预测中的估计误差对矿产资源的开发和利用是至关重要的.克立格法被认为是最佳的品位估计方法，其必须满足对于品位空间分布的平稳性和内蕴假设.但实践上，大部分的品位数据具有稀疏、不规则而复杂的空间分布，这有时会导致克立格法违反平稳性和内蕴假设.本文提出基于多基因遗传规划的矿石品位估计方法，并将其与克立格法进行对比.结果显示，基于多基因遗传规划的方法不需要关于空间分布的假设.这样，简化了实施矿体品位预测的条件，并能取得较好的预测结果，可应用于复杂矿体品位的预测.
Abstract：Ore grade estimation is relatively difficult due to the complexity of ore deposit formation process and numerous control factors. Evaluation of ore deposit with low estimation error is crucial in mineral resources development and usage. So far， Kriging， now known as a best estimation method of grade， is based on intrinsic assumption and stationarity about the underlying grade spatial distribution. However， most of ore grade data are spatially sparse， irregularly spaced and have complex distribution， which could result in the Kriging estimation method violating intrinsic assumption and stationarity. This article presented a new method for ore grade estimation based on multi-gene genetic programming and also compared it with ordinary Kriging. The results show that the proposed method makes no assumptions about the spatial distribution of grade data， the condition of implementing ore body grade prediction is simplified， and it can achieve better prediction effect. So， the proposed method can be used to estimate ore grade for complex ore deposit.