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加权Logistic回归模型在斑岩铜矿预测中的应用——以中—哈边境扎尔玛—萨吾尔成矿带为例
引用本文:努丽曼古·阿不都克力木,张晓帆,陈川,徐仕琪,赵同阳.加权Logistic回归模型在斑岩铜矿预测中的应用——以中—哈边境扎尔玛—萨吾尔成矿带为例[J].地质论评,2012,58(2):396-400.
作者姓名:努丽曼古·阿不都克力木  张晓帆  陈川  徐仕琪  赵同阳
作者单位:新疆大学新疆中亚造山带大陆动力学与成矿预测重点实验室, 乌鲁木齐, 830047;新疆大学新疆中亚造山带大陆动力学与成矿预测重点实验室, 乌鲁木齐, 830047;新疆大学新疆中亚造山带大陆动力学与成矿预测重点实验室, 乌鲁木齐, 830047;新疆地质调查院,乌鲁木齐, 830000;新疆地质调查院,乌鲁木齐, 830000
基金项目:本文为国家“十二·五”科技支撑计划“新疆重要成矿带战略性矿产资源预测与靶区评价”(编号2011BAB06B08)、国家重点基础研究发展计划项目“中亚造山带大陆动力学与成矿作用”(编号 2007CB411308)的成果。
摘    要:加权Logistic回归是基于GIS成矿预测的主要方法之一,其模型是不同于线性模型的一种类型。它具有强大的空间分析功能、适用性强、不受任何独立条件的约束、预测结果更可靠,因此在矿产资源评价研究中得到了很多地质学家的青睐。以矿床模型和成矿理论为基础,加权Logistic回归分析模型在成矿预测中的应用主要包括三部分:加权Logistic回归模型的建立及其应用、成矿有利度综合评价、成矿远景区圈定。本文以中国—哈萨克斯坦边境地区扎尔玛—萨吾尔成矿带斑岩型铜矿为例,探讨了基于GIS的加权Logistic回归模型在成矿预测中的应用。

关 键 词:扎尔玛—萨吾尔  GIS  加权Logistic回归  成矿预测

The Application of Weighted Logistic Regression Model in Prediction of Porphyry Copper Deposit——take Zharma—Sawur metallogenic belt,China—Kazakhstan border area,as an example
Nulimangu ABUDUKELIMU,ZHANG Xiaofan,CHEN Chuan,XU Shiqi,ZHAO Tongyang.The Application of Weighted Logistic Regression Model in Prediction of Porphyry Copper Deposit——take Zharma—Sawur metallogenic belt,China—Kazakhstan border area,as an example[J].Geological Review,2012,58(2):396-400.
Authors:Nulimangu ABUDUKELIMU  ZHANG Xiaofan  CHEN Chuan  XU Shiqi  ZHAO Tongyang
Institution:1) Xinjiang Key Laboratory for Geodynamic Processes and Metalloginic Prognosis of the Central Asian Orogenic Belt,Xinjiang University,Urumqi, 830047; 2) Xinjiang Geological Survey Academy,Urumqi, 830000
Abstract:Weighted Logistic Regression is one of the main methods of mineral potential mapping. It is different from linear model. Because of its powerful spatial analysis function, strong adaptability, unconstrained by independent conditions, and more reliable prediction results, Weighted Logistic Regression is widely used by many geologists in mineral resources assessment. Based on the mineral deposit model and theory, Weighted Logistic Regression is consists of three parts: (1)Establishment of weighted logistic regression model for mineral potential mapping;(2)comprehensive evaluation of favorable degrees;(3)mineral potential mapping of study area. By the Weighted Logistic Regression model for mineral potential mapping, Zharma—Sawur Metallogic Belt which across border region of China and Kazakhstan is studied and mineral prospecting area of porphyry copper deposit is mapped. At the end, the availability of Weighted Logistic Regression Model for mineral potential mapping is discussed.
Keywords:Zharma—Sawur Metallogic Belt  GIS  weighted logistic regression model  mineral potential mapping
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