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| 南亚地缘环境风险等级的智能判别与分析 | |
| 引用本文： | 林刚,丁方宇,付晶莹,杨雪菲,韩权. 南亚地缘环境风险等级的智能判别与分析[J]. 科技导报(北京), 2018, 36(3): 70-74. DOI: 10.3981/j.issn.1000-7857.2018.03.009 |
| 作者姓名： | 林刚 丁方宇 付晶莹 杨雪菲 韩权 |
| 作者单位： | 1. 中国科学院地理科学与资源研究所, 北京 100101; 2. 中国科学院大学资源与环境学院, 北京 100049; 3. 长安大学地球科学与资源学院, 西安 710064; 4. 中国矿业大学(北京)地球科学与测绘工程学院, 北京 100083 |
| 基金项目： | 中国博士后科学基金第61批面上项目（2017M610974）;中国科学院重点部署项目（ZDRW-ZS-2016-6-1） |
| 摘 要： | 地缘环境安全受到地形、气候、资源等自然要素的制约,也受到民族、宗教、文明、意识形态、政治制度、发展水平等差异的影响。基于地缘风险系统理论,梳理了历史研究成果,确立了地缘风险评价指标体系。以最新建立的多尺度、多数据源的全球地缘环境数据库为本底,以南亚为典型区域,构建了基于机器学习算法的地缘风险智能评价模型。 |
| 关 键 词： | 中巴经济走廊 地缘风险 智能判别 机器学习 |
| 收稿时间： | 2017-11-12 |
Intelligent recognition of risk levels of geopolitical system for South Asia |
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| LIN Gang,DING Fangyu,FU Jingying,YANG Xuefei,HAN Quan. Intelligent recognition of risk levels of geopolitical system for South Asia[J]. Science & Technology Review, 2018, 36(3): 70-74. DOI: 10.3981/j.issn.1000-7857.2018.03.009 | |
| Authors: | LIN Gang DING Fangyu FU Jingying YANG Xuefei HAN Quan |
| Affiliation: | 1. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 2. College of Resource and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; 3. School of Earth Science and Resource, Chang'an University, Xi'an 710064, China; 4. College of Geoscience and Surveying Engineering, China University of Mining & Technology(Beijing), Beijing 100083, China |
| Abstract: | A fast and accurate recognition of risk levels of geopolitical system for the typical regions of "the Belt and Road Initiative" can provide scientific support for the geopolitical strategy. The geopolitical system is not only influenced by climate and geographic environment but also hemmed by nationality, religion, civilization, ideology, political system and development level. Solutions to those problems not only depend on interdisciplinary work but also need cross-border study. Based on the geosystem theory, this paper makes a systematic study of literature, and firstly presents an evaluation index system for geopolitical risks. Then, it provides a machine learning method to evaluate the geopolitical risk levels of South Asia region based on the multiscale and multidata sources global geo-environment database. It is expected to provide a scientific support for the China Pakistan Economic Corridor(CPEC). |
| Keywords: | CPEC geopolitical risks intelligent recognition machine learning |
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