Precipitation Complexity Measurement Using Multifractal Spectra Empirical Mode Decomposition Detrended Fluctuation Analysis

被引：24
作者：
Liu, Dong [1 ,2 ,3 ,4 ]
Luo, Mingjie [1 ]
Fu, Qiang [1 ]
Zhang, Yongjia [1 ]
Imran, Khan M. [1 ]
Zhao, Dan [1 ]
Li, Tianxiao [1 ]
Abrar, Faiz M. [1 ]
机构：
[1] Northeast Agr Univ, Sch Conservancy & Civil Engn, Harbin 150030, Heilongjiang, Peoples R China
[2] Northeast Agr Univ, Key Lab Effect Utilizat Agr Water Resources, Minist Agr, Harbin 150030, Heilongjiang, Peoples R China
[3] Northeast Agr Univ, Heilongjiang Prov Collaborat Innovat Ctr Grain Pr, Harbin 150030, Heilongjiang, Peoples R China
[4] Northeast Agr Univ, Key Lab Water Saving Agr Ordinary Univ Heilongjia, Harbin 150030, Heilongjiang, Peoples R China
来源：
WATER RESOURCES MANAGEMENT | 2016年 / 30卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Anti-noise capability; Complexity measurement; Detrended fluctuation analysis; Empirical mode decomposition; Harbin precipitation; Multifractal spectra; HYDROLOGY; SIGNALS;
D O I：
10.1007/s11269-015-1174-9
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
The stability of current methods of complexity measurement are generally Inefficient. In this study, multifractal spectra (MFS) analysis, which depends on empirical mode decomposition detrended fluctuation analysis (EMD-DFA), was used to measure the complexity of the monthly precipitation series from 1964 to 2013 (50 years) of 11 districts in Harbin, Heilongjiang Province, China. By comparing the anti-noise capability of MFS-EMD-DFA with that of conventional complexity measurement approaches, such as sample entropy, Lempel-Ziv complexity, and approx mate entropy, it was established that MFS-EMD-DFA has greater robustness in anti-noise jamming, and thus it could be applied more widely. The precipitation series complexity strength map of the 11 regions was drawn using a geographical information system. This study analyzed the correlation between precipitation and some meteorological factors and then ranked their strengths. The results showed that many meteorological factors have strong connections with the regional precipitation series in the study area. This study provided a solid foundation for further extraction of hydrological information in Harbin and proposed a new method for complexity analysis. The novel MFS-EMD-DFA approach could also be applied to the analysis of multifractal characteristics as well as complexity measurement in various other disciplines.
引用
收藏
页码：505 / 522
页数：18
相关论文
共 29 条
[1]   Analysis of EEG background activity in Alzheimer's disease patients with Lempel-Ziv complexity and central tendency measure [J].
Abásolo, D ;
Hornero, R ;
Gómez, C ;
García, M ;
López, M .
MEDICAL ENGINEERING & PHYSICS, 2006, 28 (04) :315-322
[2]   Fractal dimensions for rainfall time series [J].
Breslin, MC ;
Belward, JA .
MATHEMATICS AND COMPUTERS IN SIMULATION, 1999, 48 (4-6) :437-446
[3]   Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA [J].
Cao, Guangxi ;
Cao, Jie ;
Xu, Longbing .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2013, 392 (04) :797-807
[4]   Complexity of Snow Schemes in a Climate Model and Its Impact on Surface Energy and Hydrology [J].
Dutra, Emanuel ;
Viterbo, Pedro ;
Miranda, Pedro M. A. ;
Balsamo, Gianpaolo .
JOURNAL OF HYDROMETEOROLOGY, 2012, 13 (02) :521-538
[5]   Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives [J].
He, Ling-Yun ;
Chen, Shu-Peng .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2010, 389 (16) :3218-3229
[6]   Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions [J].
He, Zhenfang ;
Zhang, Yaonan ;
Guo, Qingchun ;
Zhao, Xueru .
WATER RESOURCES MANAGEMENT, 2014, 28 (15) :5297-5317
[7]  
HENDERSON-SELLERS A, 1990, ATMOSFERA, V3, P183
[8]   Analysis of biomedical signals by the Lempel-Ziv complexity: the effect of finite data size [J].
Hu, Jing ;
Gao, Jianbo ;
Principe, Jose C. .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2006, 53 (12) :2606-2609
[9]   The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J].
Huang, NE ;
Shen, Z ;
Long, SR ;
Wu, MLC ;
Shih, HH ;
Zheng, QN ;
Yen, NC ;
Tung, CC ;
Liu, HH .
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971) :903-995
[10]   Multifractal detrended fluctuation analysis of nonstationary time series [J].
Kantelhardt, JW ;
Zschiegner, SA ;
Koscielny-Bunde, E ;
Havlin, S ;
Bunde, A ;
Stanley, HE .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2002, 316 (1-4) :87-114
123