Diagnostic Complexity of Regional Groundwater Resources System Based on time series fractal dimension and Artificial Fish Swarm Algorithm
Diagnostic Complexity of Regional Groundwater Resources System Based on time series fractal dimension and Artificial Fish Swarm Algorithm
复制标题
基于时间序列分维和人工鱼群算法的区域地下水资源系统复杂性诊断
DOI：
10.1007/s11269-013-0257-8
复制
发表时间：
2013-05-01
影响因子：
4.3
通讯作者：
Bazimenyera, Jean de Dieu
中科院分区：
文献类型：
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作者：
Yu, Miao;Liu, Dong;Bazimenyera, Jean de Dieu
由于经济发展和人口增长，建三江地下水资源受到人为和自然因素的双重影响。为了实现水资源的局部优化配置，促进地方经济发展，一种合适的地下水资源系统复杂性度量方法是非常重要的。将基于曲线长度计算的时间序列分形维数与人工鱼算法相结合，对建三江地下水序列进行智能高效拟合。计算了建三江分支局15个区月地下水埋深序列的分维值及其平均复杂度，结果表明，北区地下水埋深序列的复杂度最高，南区地下水埋深序列的复杂度最低。研究结果表明，人类活动是影响区域地下水埋深动态变化的最重要因素，并证实了分形理论与人工鱼算法相结合提取水文时间序列复杂性特征的可行性，可应用于区域水文过程的研究。为实现区域地下水资源的可持续利用提供了科学依据。
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 groundwater 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.