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黄金科学技术 ›› 2018, Vol. 26 ›› Issue (3): 372-378.doi: 10.11872/j.issn.1005-2518.2018.03.372

• 采选技术与矿山管理 • 上一篇    下一篇

基于PCA和GM(1,1)的矿山生态环境预测模型

周智勇1,2,肖玮1,陈建宏1,李欢1   

  1. 1.中南大学资源与安全工程学院,湖南 长沙 410083;
    2.湖南辰州矿业博士后协作研发中心,湖南 怀化 419607
  • 收稿日期:2017-04-06 修回日期:2017-06-02 出版日期:2018-06-30 发布日期:2018-08-24
  • 作者简介:周智勇(1980-),男,江西上饶人,博士,讲师,从事数字矿山、矿业系统工程及矿山安全与环保方面的研究工作。csuzzy@126.com
  • 基金资助:
    中南大学研究生自主探索创新项目“基于PCA和GM(1,1)的矿山生态环境预测模型”(编号:2017zzts242)、国家自然科学基金“基于属性驱动的矿体动态建模及更新方法研究”(编号:51504286)、“地下金属矿采掘计划可视化优化方法与技术研究”(编号:51374242)、中国博士后科学基金资助项目“地矿工程三维实体模型动态构建及更新方法研究”(编号:2015M572270)和湖南省科技计划项目“复杂矿井通风系统三维可视化仿真模拟及优化技术研究”(编号:2015RS4004)联合资助
     

Prediction Model of Mine Ecological Environment Based on PCA and GM(1,1)

ZHOU Zhiyong 1,2,XIAO Wei 1,CHEN Jianhong 1,LI Huan 1   

  1. 1.School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China;2.Postdoctoral Collaborative Research Center,Hunan Chenzhou Mining,Huaihua 419607,Hunan,China
  • Received:2017-04-06 Revised:2017-06-02 Online:2018-06-30 Published:2018-08-24

摘要: 矿山开采过程中产生的生态环境污染问题日益突出,针对矿山生态环境的预测评价显得尤为重要。综合运用主成分分析法、灰色预测模型和初等关联函数等方法构建矿山生态环境预测模型,可以为矿业企业在未来环境保护及环保投资提供指导与借鉴。首先综合考虑环保资金投入和采矿、选矿对环境及员工的影响构建生态环境评价指标体系。主成分提取后,选取方差贡献率较高的主成分计算分析,可以得到2016年实际得分分别为-4.1776、0.4093、-0.2553以及2016年预测得分分别为-4.2926、-0.2175、0.3312。2016年生态环境评价值为-0.8861,预测值为-0.9708,2017年和2018年的预测评价值为-1.5493、-2.0511。研究结果表明:预测数据与实际数据基本一致,验证了预测模型的有效性,该矿山区域生态环境在持续改善。

关键词: 矿山, 主成分分析, 灰色预测模型, 关联函数, 生态环境预测, 定量分析, 评价指标体系

Abstract: The problem of ecological environment pollution is becoming more and more serious,so it is very important to forecast and evaluate the ecological environment of mine.The prediction model of mine ecological environment was established by using principal component analysis,grey prediction model and elementary correlation function,it can provide guidance and reference for mining companies about environment protection and environmental protection investment in the future.Comprehensively consider the impact of environmental protection funds,mining and mineral processing on the environment and employees to construct the ecological environment evaluation index system.Analyzed the principal component with higher difference contribution rate after extraction of principal components,we can get the actual scores in 2016 are -4.1776,0.4093,-0.2553,and the forecast scores in 2016 are -4.2926,-0.2175,0.3312 respectively.The evaluation value of ecological environment in 2016 is -0.8861 and the forecast value is -0.9708.The predictive value of ecological environment in 2017 is -1.5493 and in 2018 is -2.0511.The results show that the predicted data are consistent with the actual data and the validity of the model is verified,the ecological environment of the mine is continuously improving.

Key words: mine, principal component analysis, gray prediction model, correlation function, ecological envi-ronment prediction, quantitative analysis, evaluation index system

中图分类号: 

  • X826 
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