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- In this paper, the wavelet multiple time scales analysis method was used to analyze annual runoff time series from 1882 to 2006 of Yichang Hydrological Station. 运用小波分析的多分辨率功能，对宜昌水文站1882-2006年年径流量时间序列资料进行了多时间尺度分析。
- Through analyzing problem of wavelet analysis,the annual runoff time series from 1956 to 2000 of Hejin hydrological station in Fen River are decomposed into multiple time-scale series with EMD method. 针对小波分析的不足之处,运用EMD法对汾河河津水文站还原后的天然径流量时序进行多时间尺度分析,并揭示了各分量的趋势变化及影响因素。
- characteristics of runoff time series 径流时序特征
- Application of Nonparametric Disaggregation Model for Stochastic Simulation of Daily Runoff Time Series in Flood Period 非参数解集模型在汛期日径流随机模拟中的应用
- Scale Invariant Analysis and Runoff Trend Prediction of the Runoff Time Series in the Yellow River 黄河径流序列标度不变性分析及趋势预测研究
- Hybrid Stochastic Model Base on Wavelet Analysis and Its Application in Prediction of Runoff Time Series 基于小波分析的组合随机模型及其在径流预测中的应用
- Research on Period of Runoff Time Series in the Upper Reach of the Yellow River Based on Wavelet Analysis 基于小波分析的黄河上游径流变化周期研究
- runoff time series 径流序列
- annual runoff time series 年径流时间序列
- monthly runoff time series 月径流时间序列
- chaotic runoff time series 混沌径流时间序列
- This is called a deseasonalizing time series. 这叫调和时间数列。
- Time Series Analysis Hamilton J.D. 时间序列分析。
- Predicts the future values for a time series. 预测一个时序的未来值。
- Results A new mode of time series is established. 结果建立了一个新的时间序列模型。
- Application of wavelet transform to monthly runoff time serial analysis in Zagunao watershed,the upper Minjiang River. 小波变换在岷江上游杂古脑流域径流时间序列分析中的应用
- Noise in the hydrological time series influences not only the hydrology chaos identification, but also the runoff prediction precision. 摘要水文要素时间序列中的噪声不仅影响水文混沌特性识别，更影响径流预测精度。
- The application of the proposed model to predict the monthly runoff shows that it can effectively dealing with the complicated hydrological time series with preferable precision. 实例表明，该模型能较好地处理复杂的水文数据序列，且有较好的预测精度。
- Tab to display the tree view of the time series model. 选项卡可以显示时序模型的树视图。
- Returns predicted future or historical values for time series data. 返回时序数据的将来或历史的预测值。
