资源与产业 ›› 2010, Vol. 12 ›› Issue (3): 66-70.

• 资源评价 • 上一篇    下一篇

基于熵权法的矿产资源竞争力比较评价

付海波1,孔锐1,2   

  1. (1中国地质大学 人文经管学院,北京 100083;
    2中国地质大学 资源与环境管理实验室,北京 100083)
  • 收稿日期:2009-10-26 修回日期:2010-04-21 出版日期:2010-06-20 发布日期:2010-06-20
  • 作者简介:付海波(1986— ),男,硕士生,主要从事企业管理研究。E-mail:fhb7003423@163.com

COMPARATIVE EVALUATION ON MINERAL RESOURCES COMPETITIVENESS BASED ON ENTROPY WEIGHT METHOD

 FU  Hai-bo 1, KONG  Rui 1,2   

  1. (1. School of Humanities and Economic Management, China University of Geosciences, Beijing 100083, China;
     2. Resource and Environmental Management Laboratory, China University of Geosciences, Beijing 100083, China)
  • Received:2009-10-26 Revised:2010-04-21 Online:2010-06-20 Published:2010-06-20

摘要:

矿产资源是国家建设的重要物质基础,是经济社会可持续发展的必要保障。科学准确地进行矿产资源评价,可以为国家或地区制定相关政策提供科学依据。在进行矿产资源竞争力比较评价时,大多数学者选用了模糊综合评判法,这一方法对资源竞争力这类既包含定量又包含定性因素的模糊概念的评判具有很高的适用性,但在某些情况下也存在着一定的缺陷。本文在前人进行矿产资源竞争力比较评价的基础之上,使用其现有数据,将熵权法引入了矿产资源竞争力评价领域,论证了熵权法在矿产资源竞争力评价领域的实用性,和其独特的价值,并解决了在运用模糊综合评判法进行矿产资源竞争力比较评价时可能遇到的两大难题。

关键词: 矿产资源, 竞争力, 熵权法

Abstract:

Mineral resources as an important material foundation of national construction are essential guarantee for sustainable development of economy and society. A scientific and accurate evaluation of mineral resources can provide a scientific basis for the development of relevant policies. While carrying out comparative assessment of the competitiveness of mineral resources, most scholars use the fuzzy comprehensive evaluation method, which is very useful to evaluate vague concepts, like resources competitiveness which contains both quantitative and qualitative factors. This paper, based on the predecessors' studies on mineral resources competitiveness evaluation, introduces a new method entropy weight method to process the same data. Though deficiencies, entropy weight method is valued in the field of mineral resources competitiveness evaluation, which can deal with two challenges that the traditional method, fuzzy comprehensive evaluation method, is facing.

Key words: mineral resources, competitiveness, entropy weight method

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