Risk Evaluation of Overseas Mining Investment Based on a Support Vector Machine

被引：3
作者：
He, Hujun [1 ,2 ]
Zhao, Yichen [1 ]
Tian, Hongxu [1 ]
Li, Wei [1 ]
机构：
[1] Changan Univ, Sch Earth Sci & Resources, Xian 710054, Peoples R China
[2] Minist Educ, Key Lab Western Mineral Resources & Geol Engn, Xian 710054, Peoples R China
来源：
SUSTAINABILITY | 2023年 / 15卷 / 01期
关键词：
support vector machine; overseas investment; risk evaluation; training sample; South Africa;
D O I：
10.3390/su15010240
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Analyzing the general method of establishing a support vector machine evaluation model, this paper discusses the application of this model in the risk assessment of overseas mining investment. Based on the analysis of the risk assessment index system of overseas mining investment, the related parameters of the optimal model were ascertained by training the sample data of 20 countries collected in 2015 and 2016, and the investment risk of 8 test samples was evaluated. All 8 samples were correctly identified, with an error rate of 0. South Africa's mining investment risk in 2016 was assessed using the risk evaluation model for overseas mining investment based on a support vector machine, and it was rated as grade IV (general investment risk). The results show that the model can provide a new solution for the judgment and deconstruction of the risk of overseas mining investment.
引用
收藏
页数：14
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