Articles | Volume 22, issue 4
https://doi.org/10.5194/npg-22-371-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-22-371-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Improved singular spectrum analysis for time series with missing data
Y. Shen
CORRESPONDING AUTHOR
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
F. Peng
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
Center for Spatial Information Science and Sustainable Development, Shanghai, China
B. Li
College of Surveying and Geo-informatics, Tongji University, Shanghai, China
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Subject: Time series, machine learning, networks, stochastic processes, extreme events | Topic: Solid earth, continental surface, biogeochemistry
Multifractal structure and Gutenberg–Richter parameter associated with volcanic emissions of high energy in Colima, Mexico (years 2013–2015)
Extraction of periodic signals in Global Navigation Satellite System (GNSS) vertical coordinate time series using the adaptive ensemble empirical modal decomposition method
Stability and uncertainty assessment of geoelectrical resistivity model parameters: a new hybrid metaheuristic algorithm and posterior probability density function approach
Application of Lévy processes in modelling (geodetic) time series with mixed spectra
Seismic section image detail enhancement method based on bilateral texture filtering and adaptive enhancement of texture details
A fast approximation for 1-D inversion of transient electromagnetic data by using a back propagation neural network and improved particle swarm optimization
Negentropy anomaly analysis of the borehole strain associated with the Ms 8.0 Wenchuan earthquake
Mahalanobis distance-based recognition of changes in the dynamics of a seismic process
Denoising stacked autoencoders for transient electromagnetic signal denoising
Simple statistics for complex Earthquake time distributions
Non-linear effects of pore pressure increase on seismic event generation in a multi-degree-of-freedom rate-and-state model of tectonic fault sliding
Sandpile-based model for capturing magnitude distributions and spatiotemporal clustering and separation in regional earthquakes
Foreshocks and short-term hazard assessment of large earthquakes using complex networks: the case of the 2009 L'Aquila earthquake
Recent seismic activity at Cephalonia (Greece): a study through candidate electromagnetic precursors in terms of non-linear dynamics
Static behaviour of induced seismicity
Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model
Earthquake sequencing: chimera states with Kuramoto model dynamics on directed graphs
Search for the 531-day-period wobble signal in the polar motion based on EEMD
Marisol Monterrubio-Velasco, Xavier Lana, and Raúl Arámbula-Mendoza
Nonlin. Processes Geophys., 31, 449–461, https://doi.org/10.5194/npg-31-449-2024, https://doi.org/10.5194/npg-31-449-2024, 2024
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Understanding volcanic activity is crucial for uncovering the fundamental physical mechanisms governing this natural phenomenon. In this study, we show the application of multifractal and statistical analysis to investigate changes associated with volcanic activity. We aim to identify significant variations within the physical processes related to changes in volcanic activity. These methodologies offer the potential to identify pertinent changes preceding a high-energy explosion.
Weiwei Li and Jing Guo
Nonlin. Processes Geophys., 31, 99–113, https://doi.org/10.5194/npg-31-99-2024, https://doi.org/10.5194/npg-31-99-2024, 2024
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Improper handling of missing data and offsets will affect the accuracy of a signal of interest. The trend in GNSS belonging to GLOSS is key to getting the absolute sea level. However, this is affected by the periodic signals that are included. Although adaptive EEMD is capable of extracting periodic signals, missing data and offsets are ignored in previous work. Meanwhile, the time-varying periodic characteristics derived by adaptive EEMD are more conducive to analyzing the driving factors.
Kuldeep Sarkar, Jit V. Tiwari, and Upendra K. Singh
Nonlin. Processes Geophys., 31, 7–24, https://doi.org/10.5194/npg-31-7-2024, https://doi.org/10.5194/npg-31-7-2024, 2024
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We evaluated three meta-heuristic algorithms using resistivity data. An enormous solution is assessed and the best-fitted solutions are chosen. The posterior probability density function with a 68.27 % confidence interval, a mean and posterior solution, and correlation and covariance matrix were calculated for the assessment of the uncertainty, stability, and mean model. We found that vPSOGWO provides reliable and consistently better results that are correlated well with borehole information.
Jean-Philippe Montillet, Xiaoxing He, Kegen Yu, and Changliang Xiong
Nonlin. Processes Geophys., 28, 121–134, https://doi.org/10.5194/npg-28-121-2021, https://doi.org/10.5194/npg-28-121-2021, 2021
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Recently, various models have been developed, including the
fractional Brownian motion (fBm), to analyse the stochastic properties of
geodetic time series, together with the estimated geophysical signals.
The noise spectrum of these time series is generally modelled as a mixed
spectrum, with a sum of white and coloured noise. Here, we are interested
in modelling the residual time series after deterministically subtracting geophysical signals from the observations with the Lévy processes.
Xiang-Yu Jia and Chang-Lei DongYe
Nonlin. Processes Geophys., 27, 253–260, https://doi.org/10.5194/npg-27-253-2020, https://doi.org/10.5194/npg-27-253-2020, 2020
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We proposed a texture detail enhancement method for seismic section image. Wavelet transform can effectively separate structure information and detail information of an image. High-frequency noise in structural information can be estimated and removed effectively by using bilateral texture filter in a low-frequency sub-band. In the high-frequency sub-band, adaptive enhancement transform can be used to enhance the image edge and texture information and effectively remove the low-frequency noise.
Ruiyou Li, Huaiqing Zhang, Nian Yu, Ruiheng Li, and Qiong Zhuang
Nonlin. Processes Geophys., 26, 445–456, https://doi.org/10.5194/npg-26-445-2019, https://doi.org/10.5194/npg-26-445-2019, 2019
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The chaotic-oscillation inertia weight back propagation (COPSO-BP) algorithm is proposed for transient electromagnetic inversion. The BP's initial weight and threshold parameters were trained by COPSO, overcoming the BP falling into a local optimum. Inversion of the layered geoelectric model showed that the COPSO-BP method is accurate and stable and needs less training time. It can be used in 1-D direct current sounding, 1-D magnetotelluric sounding, seismic-wave impedance and source detection.
Kaiguang Zhu, Zining Yu, Chengquan Chi, Mengxuan Fan, and Kaiyan Li
Nonlin. Processes Geophys., 26, 371–380, https://doi.org/10.5194/npg-26-371-2019, https://doi.org/10.5194/npg-26-371-2019, 2019
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Negentropy anomalies of borehole strain associated with the Wenchuan earthquake are analysed. The cumulative anomalies are studied on both large and small scales. Through a comparison discussion, we compare the cumulative anomalies of different time periods and stations with those at the Guza station during the study period and preliminarily exclude meteorological factors. We suspect negentropy anomalies at the Guza station to have recorded abnormal changes related to the Wenchuan earthquake.
Teimuraz Matcharashvili, Zbigniew Czechowski, and Natalia Zhukova
Nonlin. Processes Geophys., 26, 291–305, https://doi.org/10.5194/npg-26-291-2019, https://doi.org/10.5194/npg-26-291-2019, 2019
Fanqiang Lin, Kecheng Chen, Xuben Wang, Hui Cao, Danlei Chen, and Fanzeng Chen
Nonlin. Processes Geophys., 26, 13–23, https://doi.org/10.5194/npg-26-13-2019, https://doi.org/10.5194/npg-26-13-2019, 2019
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The deep-seated information is reflected in the late-stage data of the second field. By introducing the deep learning algorithm integrated with the characteristics of the secondary field data, we can map the contaminated data in late track data to a high-probability position. By comparing several filtering algorithms, the SFSDSA method has better performance and the denoising signal is conducive to further improving the effective detection depth.
Teimuraz Matcharashvili, Takahiro Hatano, Tamaz Chelidze, and Natalia Zhukova
Nonlin. Processes Geophys., 25, 497–510, https://doi.org/10.5194/npg-25-497-2018, https://doi.org/10.5194/npg-25-497-2018, 2018
Sergey B. Turuntaev and Vasily Y. Riga
Nonlin. Processes Geophys., 24, 215–225, https://doi.org/10.5194/npg-24-215-2017, https://doi.org/10.5194/npg-24-215-2017, 2017
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The influence of fluid injection on tectonic fault sliding and generation of seismic events was studied in the paper by a multi-degree-of-freedom rate-and-state friction model with a two-parametric friction law. The considered system could exhibit different types of motion. The main seismic activity could appear directly after the start of fluid injection or in the post-injection phase (after some days or months). Such an influence of injection on seismicity is observed in the real cases.
Rene C. Batac, Antonino A. Paguirigan Jr., Anjali B. Tarun, and Anthony G. Longjas
Nonlin. Processes Geophys., 24, 179–187, https://doi.org/10.5194/npg-24-179-2017, https://doi.org/10.5194/npg-24-179-2017, 2017
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The sandpile-based model is the paradigm model of self-organized criticality (SOC), a mechanism believed to be responsible for the occurrence of scale-free (power-law) distributions in nature. One particular SOC system that is rife with power-law distributions is that of earthquakes, the most widely known of which is the Gutenberg–Richter (GR) law of earthquake energies. Here, we modify the sandpile to be of use in capturing the energy, space, and time statistics of earthquakes simultaneously.
Eleni Daskalaki, Konstantinos Spiliotis, Constantinos Siettos, Georgios Minadakis, and Gerassimos A. Papadopoulos
Nonlin. Processes Geophys., 23, 241–256, https://doi.org/10.5194/npg-23-241-2016, https://doi.org/10.5194/npg-23-241-2016, 2016
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The monitoring of statistical network properties could be useful for short-term hazard assessment of the occurrence of mainshocks in the presence of foreshocks. Using successive connections between events acquired from the earthquake catalog of INGV for the case of the L’Aquila (Italy) mainshock (Mw = 6.3) of 6 April 2009, we provide evidence that network measures, both global (average clustering coefficient, small-world index) and local (betweenness centrality) ones, could potentially be used.
Stelios M. Potirakis, Yiannis Contoyiannis, Nikolaos S. Melis, John Kopanas, George Antonopoulos, Georgios Balasis, Charalampos Kontoes, Constantinos Nomicos, and Konstantinos Eftaxias
Nonlin. Processes Geophys., 23, 223–240, https://doi.org/10.5194/npg-23-223-2016, https://doi.org/10.5194/npg-23-223-2016, 2016
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Based on the methods of critical fluctuations and natural time, we have shown that the fracture-induced MHz electromagnetic emissions recorded by two stations in our network prior to two recent significant earthquakes that occurred in Cephalonia present criticality characteristics, implying that they emerge from a system in critical state.
Arnaud Mignan
Nonlin. Processes Geophys., 23, 107–113, https://doi.org/10.5194/npg-23-107-2016, https://doi.org/10.5194/npg-23-107-2016, 2016
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Induced seismicity is a concern for the industries relying on fluid injection in the deep parts of the Earth’s crust. At the same time, fluid injection sites provide natural laboratories to study the impact of increased fluid pressure on earthquake generation. In this study, I show that simple geometric operations on a static stress field produced by volume change at depth explains two empirical laws of induced seismicity without having recourse to complex models derived from rock mechanics.
M. S. Cavers and K. Vasudevan
Nonlin. Processes Geophys., 22, 589–599, https://doi.org/10.5194/npg-22-589-2015, https://doi.org/10.5194/npg-22-589-2015, 2015
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We introduced a new modified Markov chain model to generate a time series of the earthquake sequences from a global catalogue with an optimum time sampling of 9 days. Here, we subject the time series to a known analysis method namely an ensemble empirical mode decomposition to study the state-to-state fluctuations in each of the intrinsic mode functions. Also, we establish the power-law behaviour of the time series with the Fano factor and Allan factor used in time-correlative behaviour studies
K. Vasudevan, M. Cavers, and A. Ware
Nonlin. Processes Geophys., 22, 499–512, https://doi.org/10.5194/npg-22-499-2015, https://doi.org/10.5194/npg-22-499-2015, 2015
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Earthquake sequencing is an intriguing research topic and the dynamics involved are complex. For directed graphs that represent earthquake sequencing, the Kuramoto model yields synchronization. Inclusion of non-local effects evokes the occurrence of chimera states or the co-existence of synchronous and asynchronous behavior among earthquake zones. It is the chaotic dynamics of them resulting in certain patterns that we begin to see in the sequence of seismic events with a very simple model.
H. Ding and W. Shen
Nonlin. Processes Geophys., 22, 473–484, https://doi.org/10.5194/npg-22-473-2015, https://doi.org/10.5194/npg-22-473-2015, 2015
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A 531-day wobble (531 dW) signal is clearly detected with a mean amplitude of about 7 mas after applying the ensemble empirical mode decomposition (EEMD) to the 1962-2013 polar motion (PM) time series. This signal is also detected in the two longest available superconducting gravimeter (SG) records. Synthetic tests are carried out to explain why the 531 dW signal can only be observed in recent 30-year PM time series after using EEMD.
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