1) yearly and monthly runoff series
年月径流序列
2) monthly runoff series
月径流序列
1.
Based on the reconstruction of the chaotic dynamic space,the correlation dimension method and Lyapunov exponent method are applied to identify the chaos of monthly runoff series.
通过江桥站和丰满水库实际月径流序列的预测结果表明,月径流序列中存在着一定的混沌特征。
2.
It takes the ideal hydrology time series as the simulation foundation,the monthly runoff series of Heshui Reservoir and the abrupt change points of elimination cycle ingredient monthly runoff series counted by Heuristic segmentation algorithm to indicate the method is feasible and superior for studying the abrupt change of hydrological time series.
以理想的水文时间序列为仿真基础,结合合水水库的月径流序列,采用启发式分割算法得出去除周期成分后的月径流序列的突变点,以此证明了启发式分割算法检测水文时间序列突变的可行性和优越性。
3) annual runoff series
年径流序列
1.
This paper analyses firstly the periods and significance of annual runoff series using methods of squance deviation and fuzzy assumption tests.
因此,利用实测入站(库)年径流序列,通过时间外推来预报未来的径流。
2.
Based on the principle of power spectrum and maximum entropy spectral analysis,this paper identified the annual runoff series periods of 12 differernt stations in Shanbei area.
基于功率谱和极大熵谱分析原理,进行了陕北地区12个测站的年径流序列的周期识别。
4) monthly runoff time series
月径流时间序列
1.
Chaos analysis of the monthly runoff time series in Jinsha River,China;
金沙江流域月径流时间序列的混沌分析
6) Year or month runoff
年月径流
补充资料：年月
1.年和月，泛指时间。 2.时代。 3.岁月;日子。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条