Weiqiang Zhu
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View article: Application of automatic differentiation to the inversion of nonlinear mantle rheology using plate motion and topography
Application of automatic differentiation to the inversion of nonlinear mantle rheology using plate motion and topography Open
The rheological properties of the mantle govern plate tectonics and mantle convection, yet constraining the rheological parameters remains a significant challenge. Laboratory experiments are usually performed under different temperature-pr…
View article: Performance of the Deep-Learning Phase Picker PhaseNet on Magnitude 3+ Earthquakes in Southern California
Performance of the Deep-Learning Phase Picker PhaseNet on Magnitude 3+ Earthquakes in Southern California Open
View article: Improvements from incorporating machine learning algorithms into near real-time operational post-processing
Improvements from incorporating machine learning algorithms into near real-time operational post-processing Open
During regional seismic monitoring, data is automatically analyzed in real-time to identify events and provide initial locations and magnitudes. Monitoring networks may apply automatic post-processing to small events (M < 3) to add and ref…
View article: DASFormer: self-supervised pretraining for earthquake monitoring
DASFormer: self-supervised pretraining for earthquake monitoring Open
View article: Fault Geometry and Source Mechanics of the Altotiberina Fault System from a High-Resolution Machine-Learning Earthquake Catalog
Fault Geometry and Source Mechanics of the Altotiberina Fault System from a High-Resolution Machine-Learning Earthquake Catalog Open
Recent advances in machine learning (ML)-based earthquake detection and location techniques combined with dense seismic networks have dramatically increased the quantity of low-magnitude earthquakes that can be detected and accurately loca…
View article: Application of automatic differentiation to the inversion of nonlinear mantle rheology using plate motion and topography
Application of automatic differentiation to the inversion of nonlinear mantle rheology using plate motion and topography Open
The rheological properties of the mantle govern plate tectonics and mantle convection, yet constraining the rheological parameters remains a significant challenge. Laboratory experiments are usually performed under different temperature-pr…
View article: An Enhanced Focal Mechanism Catalog of Induced Earthquakes in Weiyuan, Sichuan, from Dense Array Data and a Multitask Deep Learning Model
An Enhanced Focal Mechanism Catalog of Induced Earthquakes in Weiyuan, Sichuan, from Dense Array Data and a Multitask Deep Learning Model Open
Determining focal mechanisms of abundant small-magnitude (M < 3) earthquakes can better reveal subsurface fault structures and stress features, but it remains challenging due to insufficient records or inefficient methods. In the past d…
View article: A High Resolution Machine-Learning Earthquake Catalog to Characterize Fault Geometry and Source Mechanics: the Altotiberina Fault Case Study
A High Resolution Machine-Learning Earthquake Catalog to Characterize Fault Geometry and Source Mechanics: the Altotiberina Fault Case Study Open
View article: California Earthquake Dataset for Machine Learning and Cloud Computing
California Earthquake Dataset for Machine Learning and Cloud Computing Open
The San Andreas Fault system, known for its frequent seismic activity, provides an extensive dataset for earthquake studies. The region's well-instrumented seismic networks have been crucial in advancing research on earthquake statistics, …
View article: Realization of 3D coordinate estimation for spaceborne interferometric antenna
Realization of 3D coordinate estimation for spaceborne interferometric antenna Open
View article: QuakeFormer: A Uniform Approach to Earthquake Ground Motion Prediction Using Masked Transformers
QuakeFormer: A Uniform Approach to Earthquake Ground Motion Prediction Using Masked Transformers Open
Ground motion prediction (GMP) models are critical for hazard reduction before, during and after destructive earthquakes. In these three stages, intensity forecasting, early warning and interpolation models are corresponding employed to as…
View article: Deep learning for deep earthquakes: insights from OBS observations of the Tonga subduction zone
Deep learning for deep earthquakes: insights from OBS observations of the Tonga subduction zone Open
SUMMARY Applications of machine learning in seismology have greatly improved our capability of detecting earthquakes in large seismic data archives. Most of these efforts have been focused on continental shallow earthquakes, but here we in…
View article: Fiber seismic tomography of the Long Valley volcanic system
Fiber seismic tomography of the Long Valley volcanic system Open
High-resolution tomographic imaging of the subsurface structures beneath volcanic systems is fundamental to better assess their hazard and potentially estimate the amount of eruptive materials. However, obtaining such images represents a m…
View article: Phase Neural Operator for Multi‐Station Picking of Seismic Arrivals
Phase Neural Operator for Multi‐Station Picking of Seismic Arrivals Open
Seismic wave arrival time measurements form the basis for numerous downstream applications. State‐of‐the‐art approaches for phase picking use deep neural networks to annotate seismograms at each station independently, yet human experts ann…
View article: Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning
Seismic arrival-time picking on distributed acoustic sensing data using semi-supervised learning Open
Distributed Acoustic Sensing (DAS) is an emerging technology for earthquake monitoring and subsurface imaging. However, its distinct characteristics, such as unknown ground coupling and high noise level, pose challenges to signal processin…
View article: An ADMM-Based Geometric Configuration Optimization in RSSD-Based Source Localization By UAVs with Spread Angle Constraint
An ADMM-Based Geometric Configuration Optimization in RSSD-Based Source Localization By UAVs with Spread Angle Constraint Open
Deploying multiple unmanned aerial vehicles (UAVs) to locate a signal-emitting source covers a wide range of military and civilian applications like rescue and target tracking. It is well known that the UAVs-source (sensors-target) geometr…
View article: Deep Learning for Deep Earthquakes: Insights from OBS Observations of the Tonga Subduction Zone
Deep Learning for Deep Earthquakes: Insights from OBS Observations of the Tonga Subduction Zone Open
Applications of machine learning in seismology have greatly improved our capability of detecting earthquakes in large seismic data archives. Most of these efforts have been focused on continental shallow earthquakes, but here we introduce …
View article: An upper-crust lid over the Long Valley magma chamber
An upper-crust lid over the Long Valley magma chamber Open
Geophysical characterization of calderas is fundamental in assessing their potential for future catastrophic volcanic eruptions. The mechanism behind the unrest of Long Valley Caldera in California remains highly debated, with recent perio…
View article: Real-Data Testing of Distributed Acoustic Sensing for Offshore Earthquake Early Warning
Real-Data Testing of Distributed Acoustic Sensing for Offshore Earthquake Early Warning Open
We present a real-data test for offshore earthquake early warning (EEW) with distributed acoustic sensing (DAS) by transforming submarine fiber-optic cable into a dense seismic array. First, we constrain earthquake locations using the arri…
View article: Earthquake focal mechanisms with distributed acoustic sensing
Earthquake focal mechanisms with distributed acoustic sensing Open
View article: Earthquake Magnitude With DAS: A Transferable Data‐Based Scaling Relation
Earthquake Magnitude With DAS: A Transferable Data‐Based Scaling Relation Open
Distributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Previous DAS studies mainly focus on the phase information but less on the amplitude information. In this study…
View article: Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array
Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array Open
To provide important prior knowledge for the direction of arrival (DOA) estimation of UAV emitters in future wireless networks, we present a complete DOA preprocessing system for inferring the number of emitters via a massive multiple-inpu…
View article: Seismic Arrival-time Picking on Distributed Acoustic Sensing Data using Semi-supervised Learning
Seismic Arrival-time Picking on Distributed Acoustic Sensing Data using Semi-supervised Learning Open
Distributed Acoustic Sensing (DAS) is an emerging technology for earthquake monitoring and subsurface imaging. The recorded seismic signals by DAS have several distinct characteristics, such as unknown coupling effects, strong anthropogeni…
View article: Earthquake magnitude with DAS: a transferable data-based scaling relation
Earthquake magnitude with DAS: a transferable data-based scaling relation Open
Distributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Due to some instrumental limitations, current DAS studies primarily focus on the phase information but less on …
View article: QuakeFlow: a scalable machine-learning-based earthquake monitoring workflow with cloud computing
QuakeFlow: a scalable machine-learning-based earthquake monitoring workflow with cloud computing Open
SUMMARY Earthquake monitoring workflows are designed to detect earthquake signals and to determine source characteristics from continuous waveform data. Recent developments in deep learning seismology have been used to improve tasks within…
View article: RFIC 2022 Affiliation Index
RFIC 2022 Affiliation Index Open
A Capacitor Assisting Triple-Winding Transformer Low-Noise Amplifier with
View article: Automatic detection for a comprehensive view of Mayotte seismicity
Automatic detection for a comprehensive view of Mayotte seismicity Open
The seismic crisis that began in May, 2018 off the coast of Mayotte announced the onset of a volcanic eruption that started two months later 50 km southeast of the island. This seismicity has since been taken as an indicator of the volcani…
View article: Learning generative neural networks with physics knowledge
Learning generative neural networks with physics knowledge Open
View article: Toward improved urban earthquake monitoring through deep-learning-based noise suppression
Toward improved urban earthquake monitoring through deep-learning-based noise suppression Open
Earthquake monitoring in urban settings is essential but challenging, due to the strong anthropogenic noise inherent to urban seismic recordings. Here, we develop a deep-learning-based denoising algorithm, UrbanDenoiser, to filter out urba…
View article: Earthquake Phase Association Using a Bayesian Gaussian Mixture Model
Earthquake Phase Association Using a Bayesian Gaussian Mixture Model Open
Earthquake phase association algorithms aggregate picked seismic phases from a network of seismometers into individual sesimic events and play an important role in earthquake monitoring and research. Dense seismic networks and improved pha…