# Seismology and Earthquake Studies

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/seismology-and-earthquake-studies/

## Facts

| Field | Value |
| --- | --- |
| Citations | 275,351 |
| Description | This cluster of papers focuses on the application of machine learning and deep learning techniques to improve the accuracy and timeliness of earthquake early warning systems. It covers topics such as seismic signal classification, real-time seismology, convolutional neural networks for seismic phase picking, and the integration of citizen science in earthquake monitoring. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | https://openalex.org/T13018 |
| Works | 57,735 |

## Topic papers all

- [Artificial intelligence for geoscience: Progress, challenges, and perspectives](https://scholariq.org/papers/artificial-intelligence-for-geoscience-progress-challenges-and-perspectives/)
- [PAI-S/K: A robust automatic seismic P phase arrival identification scheme](https://scholariq.org/papers/pai-s-k-a-robust-automatic-seismic-p-phase-arrival-identification-scheme/)
- [Evaluation of Seismic Events Detection Algorithms](https://scholariq.org/papers/evaluation-of-seismic-events-detection-algorithms/)
- [Worldwide Statistical Correlation of Eight Years of Swarm Satellite Data with M5.5+ Earthquakes: New Hints about the Preseismic Phenomena from Space](https://scholariq.org/papers/worldwide-statistical-correlation-of-eight-years-of-swarm-satellite-data-with-m5/)
- [Predicting the Earthquake Magnitude Using the Multilayer Perceptron Neural Network with Two Hidden Layers](https://scholariq.org/papers/predicting-the-earthquake-magnitude-using-the-multilayer-perceptron-neural/)
- [RETRACTED ARTICLE: Improving earthquake prediction accuracy in Los Angeles with machine learning](https://scholariq.org/papers/retracted-article-improving-earthquake-prediction-accuracy-in-los-angeles-with/)
- [Threshold-based earthquake early warning for high-speed railways using deep learning](https://scholariq.org/papers/threshold-based-earthquake-early-warning-for-high-speed-railways-using-deep/)

## Topic researchers

Showing 12 of 20.

- [D. Brown](https://scholariq.org/researchers/d-brown/)
- [B. Krishnan](https://scholariq.org/researchers/b-krishnan/)
- [Kiyoshi Takeda](https://scholariq.org/researchers/kiyoshi-takeda/)
- [A. Vecchio](https://scholariq.org/researchers/a-vecchio/)
- [B. S. Sathyaprakash](https://scholariq.org/researchers/b-s-sathyaprakash/)
- [J. Veitch](https://scholariq.org/researchers/j-veitch/)
- [N. Christensen](https://scholariq.org/researchers/n-christensen/)
- [George Em Karniadakis](https://scholariq.org/researchers/george-em-karniadakis/)
- [S. Husa](https://scholariq.org/researchers/s-husa/)
- [S. Fairhurst](https://scholariq.org/researchers/s-fairhurst/)
- [P. R. Brady](https://scholariq.org/researchers/p-r-brady/)
- [J. T. Whelan](https://scholariq.org/researchers/j-t-whelan/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.