Integration of Density-Based Spatial Clustering with Noise and Continuous Wavelet Transform for Feature Extraction from Seismic Data

Ali, Amjad; Chen, Sheng‐Chang; Ali, Syed Haroon

doi:10.1007/s00024-022-02980-7

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…This disadvantage has also been observed in recent years. Various time-frequency tools have been applied to the analysis of earthquake time-histories, replacing the traditional Fourier transform (Lyubushin, 2021;Ali et al, 2022). Conraria and Soares (2014) used wavelet transform to characterize lagged coherence.…”

Section: Introductionmentioning

confidence: 99%

Estimation of time–frequency-dependent lagged coherence for ground motions in simulating multipoint ground motions

Wen,

2024

Preprint

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Traditional coherence functions ignore the time-varying characteristics of ground motions, influencing the accuracy of simulating multipoint nonstationary ground motions. An effective process is proposed for building the time–frequency lagged coherence expression to describe the spatial variation in both the time and frequency domains. First, the advantage of wavelet packet transform (WPT) in recognizing the time–frequency characteristics of signals is leveraged. The WPT is used to analyze the time–frequency characteristics of ground motions and estimate the time–frequency lagged coherence using the observed recordings from SMART-1 array. Then, based on the frame of simulating multipoint ground motions, a blind test for verifying the rationality of time–frequency lagged coherence is conducted to simulate spatially correlated ground motions using time–frequency and traditional lagged coherence functions. The spatial coherence of the target region is observed to have clearly lost its inherent time-varying property. The comparative results confirm the significance of using the time–frequency lagged coherence in simulating multipoint ground motions.

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Section: Introductionmentioning

confidence: 99%

Estimation of time–frequency-dependent lagged coherence for ground motions in simulating multipoint ground motions

Wen,

2024

Preprint

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Diagenesis and sequence stratigraphy of Miocene, Nyalau Formation, Sarawak, Malaysia: A case study for clastic reservoirs

Shoukat

Ali

Siddiqui

et al. 2023

Kuwait Journal of Science

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Recent advances in earthquake seismology using machine learning

Kubo,

Naoi,

Kano

2024

Earth Planets Space

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Given the recent developments in machine-learning technology, its application has rapidly progressed in various fields of earthquake seismology, achieving great success. Here, we review the recent advances, focusing on catalog development, seismicity analysis, ground-motion prediction, and crustal deformation analysis. First, we explore studies on the development of earthquake catalogs, including their elemental processes such as event detection/classification, arrival time picking, similar waveform searching, focal mechanism analysis, and paleoseismic record analysis. We then introduce studies related to earthquake risk evaluation and seismicity analysis. Additionally, we review studies on ground-motion prediction, which are categorized into four groups depending on whether the output is ground-motion intensity or ground-motion time series and the input is features (individual measurable properties) or time series. We discuss the effect of imbalanced ground-motion data on machine-learning models and the approaches taken to address the problem. Finally, we summarize the analysis of geodetic data related to crustal deformation, focusing on clustering analysis and detection of geodetic signals caused by seismic/aseismic phenomena. Graphical Abstract

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Integration of Density-Based Spatial Clustering with Noise and Continuous Wavelet Transform for Feature Extraction from Seismic Data

Cited by 3 publications

References 15 publications

Estimation of time–frequency-dependent lagged coherence for ground motions in simulating multipoint ground motions

Estimation of time–frequency-dependent lagged coherence for ground motions in simulating multipoint ground motions

Diagenesis and sequence stratigraphy of Miocene, Nyalau Formation, Sarawak, Malaysia: A case study for clastic reservoirs

Recent advances in earthquake seismology using machine learning

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