• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Water Resources Management >Diagnostic Complexity of Regional Groundwater Resources System Based on time series fractal dimension and Artificial Fish Swarm Algorithm
【24h】

Diagnostic Complexity of Regional Groundwater Resources System Based on time series fractal dimension and Artificial Fish Swarm Algorithm

机译：基于时间序列分形维和人工鱼群算法的区域地下水资源系统诊断复杂性

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

摘要

Due to the increasing high rate of economic development and population, groundwater resources of Jiansanjiang in China are affected by both anthropogenic and natural factors. In order to achieve optimal local allocation of water resources and promotion of local economic development, a suitable method for measuring the complexity of ground-water resources system is very important. In this paper, time series fractal dimension based on the curve length calculation combined with the artificial fish algorithm for the intelligent efficient fitting of data were applied to diagnose groundwater sequence in Jiansanjiang. Fractal dimension values of monthly groundwater depth series in 15 districts of Jiansanjiang Branch Bureau and their average complexity were calculated and the results revealed that the complexity of north district is the highest while that of southern district is the lowest. Our analysis also revealed that the most important influencing factor of local groundwater depth dynamics variation is the human activities and results confirmed that combined fractal theory and artificial fish algorithm for extraction hydrological time series complexity feature is feasible and can be applied in studying regional hydrological process. It also provided a scientific basis for achieving sustainable utilization of the regional groundwater resource.
机译：由于经济发展速度和人口增长率的不断提高，建三江市的地下水资源既受到人为因素的影响，也受到自然因素的影响。为了实现水资源的最优局部配置和促进当地经济发展，一种合适的测量地下水资源系统复杂性的方法非常重要。本文将基于曲线长度计算的时间序列分形维数与人工鱼群算法相结合，对数据进行智能高效拟合，对剑三江地下水位序列进行诊断。计算了剑三江市分局15个区每月地下水深度序列的分形维数值及其平均复杂度，结果表明，北部地区的复杂度最高，南部地区的复杂度最低。我们的分析还表明，当地地下水深度动态变化的最重要影响因素是人类活动，结果证明，结合分形理论和人工鱼算法提取水文时间序列复杂性特征是可行的，可用于研究区域水文过程。这也为实现区域地下水资源的可持续利用提供了科学依据。

著录项

  • 来源
    《Water Resources Management》 |2013年第7期|1897-1911|共15页
  • 作者

    Miao Yu; Dong Liu; Jean de Dieu Bazimenyera;

  • 作者单位

    School of Water Conservancy & Civil Engineering, Northeast Agricultural University,Harbin, Hcilongjiang 150030, China;

    School of Water Conservancy & Civil Engineering, Northeast Agricultural University,Harbin, Hcilongjiang 150030, China,Key Laboratory of Water-Saving Agriculture of Universities in Hcilongjiang Province,Northeast Agricultural University, Harbin, Heilongjiang 150030, China,Key Laboratory of High Efficient Utilization of Agricultural Water Resource of Ministry of Agriculture, Northeast Agricultural University, Harbin, Hcilongjiang 150030, China;

    School of Water Conservancy & Civil Engineering, Northeast Agricultural University,Harbin, Hcilongjiang 150030, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    time series fractal dimension; artificial fish swarm algorithm; groundwater depth; complexity; jiansanjiang branch bureau;

    机译：时间序列分形维数人工鱼群算法;地下水深度复杂;建三江分局;

相似文献

  • 外文文献
  • 中文文献
  • 专利
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