首页> 外文会议>International Conference on Artificial Intelligence and Computational Intelligence;AICI '09 >A New Method of Periods' Identification in Hydrologic Series Based on EEMD
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A New Method of Periods' Identification in Hydrologic Series Based on EEMD

机译:基于EEMD的水文序列周期识别新方法

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Identification of dominant periods is a very important but difficult task in hydrologic time series data analysis. In this paper, for improving the results of periodsȁ9; identification, a new method, called EEMD-MESA (ensemble empirical mode decomposition-maximum entropy spectral analysis), has been proposed, whose main idea is identifying the main intrinsic mode functions (MIMFs) in hydrologic series firstly, and then by using MESA to identify periods in each MIMFs, all periods in the hydrologic series can be gotten finally. By applying to an observed runoff series, advantages of the new method have been verified. Analyses results show that EEMD-MESA is as better as MSSA but much better than other methods (FFT and MESA); While compared with MSSA, EEMD-MESA is more convenient and time-saving. Therefore, the EEMD-MESA method would be more applicable to practical hydrologic works.
机译:在水文时间序列数据分析中,优势时段的确定是非常重要但艰巨的任务。在本文中,为了提高周期9的结果;识别,提出了一种新的方法,称为EEMD-MESA(综合经验模态分解-最大熵谱分析),其主要思想是首先识别水文序列中的主要本征模式函数(MIMF),然后通过使用MESA进行识别。确定每个MIMF的时期,水文序列的所有时期都可以最终得到。通过应用于观测到的径流序列,新方法的优点已得到验证。分析结果表明,EEMD-MESA与MSSA一样好,但比其他方法(FFT和MESA)好得多;与MSSA相比,EEMD-MESA更方便,更节省时间。因此,EEMD-MESA方法将更适用于实际的水文工作。

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