Deeplearning model to predict earthquake occurence based on realtime data
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Updated
Mar 9, 2023 - Jupyter Notebook
Deeplearning model to predict earthquake occurence based on realtime data
Homeworks for the course Earth Observation Data Analysis, 2020, Sapienza University of Rome
Kaggle challenge LANL Earthquake Prediction
Only to know whether device is on or off and state over telegram API via google app script spreadsheet
Earthquake event automatic recognizer using STA/LTA algorithm based on ObsPy lib.
A Docker tool for learning, testing, running and developing Earthworm within enclosed environments.
Was that an Earthquake?
Quake Safe Rings (QuaSaR) contains various tools to support Earthquake Early Warning (EEW) projects
An earthquake is what happens when two blocks of the earth suddenly slip past one another. By this Python Code You will know last 24 hours earthquake every details.
Cluster Analysis of Trimmed Spectrograms: framework for detection and denoising of sparse signals in time-frequency domain.
This methods can be used for event identification to detect first arrival time of Vp and Vs. These methods are Akaike Information Criterion, MER and S/L kurt
Andoid application for disaster management.
SeisT: A Foundational Deep-Learning Model for Earthquake Monitoring Tasks
Server-side releases for GlobalQuake
Detecting Earthquake P-Waves using popular STA/LTA Algorithm with visualization and estimations of Seismometer Trajectory in 3D, S-Wave arrival time and much more.
This project aims to predict the magnitude and probability of Earthquake occurring in a particular region using the historic data with various machine learning models to find which model is more accurate to accomplish this task.
A computationally efficient earthquake detection module for SeisComP
Automatic earthquake catalog building workflow: EQTransformer + Siamese EQTransformer + PickNet + REAL + HypoInverse
Construction of Long-Term Seismic Catalog with Deep Learning: A Workflow for Localized Self-Attention RNN (LoSAR)
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