金矿资源定量预测的粗糙集方法

矿产信息是各种成矿相关信息的综合体现，为了有效地提取成矿预测综合信息，有必要客观地筛选原始观测信息，突出成矿密切相关的致矿因子。粗糙集不需要数据的附加信息或先验知识，在知识库分类能力不变的前提条件下，删除无关或不重要的属性，能对决策系统进行有效约简。提出基于粗糙集理论进行集成化预测模型研究的新方法，基于粗糙集思想提取与成矿密切相关的特征矿化信息，获取最佳变量组合及区间值，并将其作为参量建立预测模型，结合经典矿床统计预测聚类方法确定代判临界值，及特征分析方法对矿产资源进行定量预测，确立了8个成矿有利单元，与研究区勘查工程资料基本吻合，表明该方法能够有效降噪，简化模型，为靶区预测提供准确的依据。

Quantitative Analysis of Gold Mineral Resource Based on Rough Set

Mineral information includes all kinds of relative metallogenic information. In order to extract comprehensive metallogenic prediction information, it's necessary to filter initial observation information to emphasize the factors which are most advantageous to metallogenic. Rough set can delete irrespective or unimportant attributes under the premises of no classification ability changing, without supplement information or prior knowledge. A new integrated predicion model based on Rough set theory is put forward in this research. The mineral information most advantageous to metallogenic from a great number of variables to achieve the optimization of variable structure and numerical interval is chosen. Based on the optimization combination, characteristic function is established for prediction. Combined with some conventional methods for deposit statistics, prediction, clustering means is applied to get the critical point for decision and quantitative charcterisic analysis is applied to predict the mineral resource by calculating the relation degree of are every geological cell. And eight geological cells are established as the cells advantageous to metallogenic. Results are basically in accord with practice, which shows availability of this method.