Name
Abstract | ||
|---|---|---|
Mineral choice optimization is a basic key issue that related to whether the entire reserve system is able to adapt to the sustainable use of national mineral resources. In this paper, we may determine indicators' weight using improved group AHP (analytic hierarchy process) combined with objective weight of each decision-maker, and according to this, the most important index is "technical difficulty of reserve", to which the government should pay more attention to. Then we added these weights into indicator variables of hierarchical clustering analysis in order to classify mineral reserve more reasonably taking the typical resources as an example, and the obtained result was consistent to the government's macroeconomic qualitative analysis. We divided typical mineral resources into four batches for reserving; among these batches, coal was taken granted as the intensive reserve object. Those scarce resources that China has advantage of should also be immediately included in the reserve object such as Tungsten, Tin, and Rare earth. To a certain extent, the results can lay foundation for the establishment of strategic reserve mechanism of mineral resources in China. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1080/10798587.2014.934588 | INTELLIGENT AUTOMATION AND SOFT COMPUTING |
Keywords | Field | DocType |
Mineral resources, Group AHP, Cluster analysis, Reserves optimization | Hierarchical clustering,Scarcity,Computer science,Dummy variable,Coal,Mineral resource classification,Artificial intelligence,Machine learning,Sustainability,Analytic hierarchy process,Environmental economics,Government | Journal |
Volume | Issue | ISSN |
20 | 4 | 1079-8587 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chaozhe Jiang | 1 | 2 | 1.52 |
| Zhaoyang Bian | 2 | 0 | 0.34 |
| Jixue Yuan | 3 | 5 | 1.63 |
| Fang Xu | 4 | 1 | 0.82 |
| Yahui Cheng | 5 | 0 | 0.34 |