Advances in Earthquake Prediction
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".
Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 2719
Special Issue Editor
Interests: earth science; seismology; seismic source; seismic hazard
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Despite the efforts made for more than 100 years to predict earthquakes, the results are rather disappointing. Knowledge of physical processes at regional and local scales prior to earthquake nucleation is poor due to the complexity and non-linearity of geosystems. Research has focused on statistical approaches to detect relevant precursory signals (seismicity, geophysical, geochemical and biological patterns). However, reported precursors are contradictory and unsuitable for rigorous statistical evaluation. Increasingly large geo-datasets and development of computationally intensive simulations provide opportunities for systematic analysis and model testing. New high-performance tools (e.g., machine learning) and multidisciplinary approaches give opportunity to assign a confidence level to each prediction.
The Special Issue promotes new ideas and approaches to answer numerous questions on earthquake prediction topics. Original research contributions are welcome from multidisciplinary fields of investigation (seismicity, geophysics and geodesy, hydrology, geochemistry, ionosphere and biological systems, etc.). Applications of advanced statistics, decision-making science, and physics of complex non-linear systems are encouraged.
Dr. Mircea Radulian
Guest Editor
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Keywords
- earthquake prediction
- earthquake precursors
- physics of faulting
- machine learning
- numerical simulations
- statistical significance
- complex non-linear systems
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