首页    期刊浏览 2024年07月07日 星期日
登录注册

文章基本信息

  • 标题:Application of BP Neural Network Model in the Evaluation of Urban Land Intensive Utilization
  • 本地全文:下载
  • 作者:Yang Xiongfei ; Yuan Xitun ; Wen YongXiao
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:248
  • 页码:3076
  • DOI:10.1051/e3sconf/202124803076
  • 出版社:EDP Sciences
  • 摘要:Using BP neural network model to analyze the urban land development status of Zhengzhou City from 2013 to 2017, the evaluation grades are divided into over-utilization, intensive use, moderate utilization and extensive utilization, and from the land input intensity, land use intensity and a total of nine indicators were selected for evaluation in three aspects of land output benefits. The results show that the urban land intensive degree of Zhengzhou City during the five years from 2013 to 2017 is 0.3039, 0.5118, 0.6189, 0.6914, 0.8509, and the intensive degree is gradually increased every year. The degree of intensive use is gradually increased every year, the evaluation level has risen from extensive use to intensive use, and the intensity of land intensive use has continued to increase.
  • 其他摘要:Using BP neural network model to analyze the urban land development status of Zhengzhou City from 2013 to 2017, the evaluation grades are divided into over-utilization, intensive use, moderate utilization and extensive utilization, and from the land input intensity, land use intensity and a total of nine indicators were selected for evaluation in three aspects of land output benefits. The results show that the urban land intensive degree of Zhengzhou City during the five years from 2013 to 2017 is 0.3039, 0.5118, 0.6189, 0.6914, 0.8509, and the intensive degree is gradually increased every year. The degree of intensive use is gradually increased every year, the evaluation level has risen from extensive use to intensive use, and the intensity of land intensive use has continued to increase.
国家哲学社会科学文献中心版权所有