...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Water policy >Water poverty assessment based on the random forest algorithm: application to Gansu, Northwest China
【24h】

Water poverty assessment based on the random forest algorithm: application to Gansu, Northwest China

机译：Water poverty assessment based on the random forest algorithm: application to Gansu, Northwest China

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相关主题

摘要

This study proposes a random forest algorithm to evaluate water poverty. It shows how the machine learning technique can beused to classify the degree of water poverty into five levels: very severe, severe, moderate, mild, and very mild. The strengths ofthe proposed random forest method include a high classification accuracy, good operational efficiency, and the ability to handlehigh-dimensional datasets. The success of the proposed method is empirically illustrated through a case study in Gansu, NorthwestChina. The analysis shows that from 2000 to 2017, the severity of water poverty in the study area declined. In 2000, mostmunicipalities were classified as level 1 (very severe) or level 2 (severe). In 2017, level 1 water poverty disappeared, with mostmunicipalities classified in as level 3 (moderate) and level 4 (mild). Spatially, there is a significant difference between the waterpoverty levels of the western, central, and eastern parts of Gansu, and the eastern part is affected by serious water povertyproblems.

著录项

获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号