SynthesisSensors (Basel, Switzerland)2023
Real-Time Seismic Intensity Measurements Prediction for Earthquake Early Warning: A Systematic Literature Review.
Synthesis in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Machine learning for prompt estimation of macroseismic intensity from seismometric data in Italy.Scientific reports · 2026Article
- Near-Real-Time Integration of Multi-Source Seismic Data.Sensors (Basel, Switzerland) · 2026Article
- Virtual Scenarios of Earthquake Early Warning to Disaster Management in Smart Cities Based on Auxiliary Classifier Generative Adversarial Networks.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
With the gradual development of and improvement in earthquake early warning systems (EEWS), more accurate real-time seismic intensity measurements (IMs) methods are needed to assess the impact range of earthquake intensities. Although traditional point source warning systems have made some progress in terms of predicting earthquake source parameters, they are still inadequate at assessing the accuracy of IMs predictions. In this paper, we aim to explore the current state of the field by reviewing real-time seismic IMs methods. First, we analyze different views on the ultimate earthquake magnitude and rupture initiation behavior. Then, we summarize the progress of IMs predictions as they relate to regional and field warnings. The applications of finite faults and simulated seismic wave fields in IMs predictions are analyzed. Finally, the methods used to evaluate IMs are discussed in terms of the accuracy of the IMs measured by different algorithms and the cost of alerts. The trend of IMs prediction methods in real time is diversified, and the integration of various types of warning algorithms and of various configurations of seismic station equipment in an integrated earthquake warning network is an important development trend for future EEWS construction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.