...
首页> 外文期刊>Computers & geosciences >Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling
【24h】

Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling

机译:预测区域图(P-A)和C-A分形分析可对矿物找矿建模的证据图进行分类和评估

获取原文
获取原文并翻译 | 示例
           

摘要

There are methods of mineral prospectivity mapping whereby, besides assignment of weights to classes of evidence in an evidential map, every evidential map is also given a weight based on expert opinion. In this regard, evaluating the relative importance of every evidential map derived from particular spatial data sets is a highly subjective exercise and the assignment of meaningful weights to evidential maps usually involves a trial-and-error procedure. In this paper, we used a prediction-area (P-A) plot and normalized density to estimate weights of every evidential map. The method of P-A plot is a data-driven way, rather than using expert opinion, to evaluate and weight evidential maps. (C) 2015 Elsevier Ltd. All rights reserved.
机译:有一些矿物远景制图的方法,通过这些方法,除了将权重分配给证据图中的证据类别之外,还根据专家意见为每个证据图赋予权重。在这方面,评估从特定空间数据集得出的每个证据图的相对重要性是一种高度主观的练习,对证据图分配有意义的权重通常涉及反复试验的过程。在本文中,我们使用了预测区域(P-A)图和归一化密度来估计每个证据图的权重。 P-A图的方法是一种数据驱动的方法,而不是使用专家意见来评估和加权证据图。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号