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Related papers: Earthquake forecasting and its verification

200 papers

Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time…

Data Analysis, Statistics and Probability · Physics 2015-06-04 Randall D. Peters , Martine Le Berre , Yves Pomeau

Earthquake nowcasting has been proposed as a means of tracking the change in large earthquake potential in a seismically active area. The method was developed using observable seismic data, in which probabilities of future large earthquakes…

Geophysics · Physics 2024-06-21 John B. Rundle , Geoffrey Fox , Andrea Donnellan , Lisa Grant Ludwig

The ranking problem of earthquake forecasts is considered. We formulate simple statistical requirements to forecasting quality measure R and analyze some R-ranking methods on this basis, in particular, the pari-mutuel gambling method by…

Geophysics · Physics 2016-04-21 G. Molchan

Ground motion scenarios exists for most of the seismically active areas around the globe. They essentially correspond to shaking level maps at given earthquake return times which are used as reference for the likely areas under threat from…

Applications · Statistics 2020-04-02 Luigi Lombardo , Hakan Tanyas

This paper describes the use of the idea of natural time to propose a new method for characterizing the seismic risk to the world's major cities at risk of earthquakes. Rather than focus on forecasting, which is the computation of…

Geophysics · Physics 2017-12-06 John B Rundle , Molly Luginbuhl , Alexis Giguere , Donald L Turcotte

A recently proposed method of constructing seismic networks from 'record breaking events' from the earthquake catalog of California (Phy. Rev. E, 77 6,066104, 2008) was successfull in establishing causal features to seismicity and arrive at…

Geophysics · Physics 2017-08-02 P. G. Revathi , T. R. Krishnamohan

The ETAS models are currently the most popular in the field of earthquake forecasting. The MCMC method is time-consuming and limited by parameter correlation while bringing parameter uncertainty. The INLA-based method "inlabru" solves these…

Applications · Statistics 2025-10-17 Ziwen Zhong

Upon employing the analysis in a new time domain, termed natural time, it has been recently demonstrated that a remarkable change of seismicity emerges before major mainshocks in California. What constitutes this change is that the…

Geophysics · Physics 2017-03-27 P. A. Varotsos , N. V. Sarlis , E. S. Skordas

The assessment of seismic risk in urban areas with high seismicity is certainly one of the most important problems that territorial managers have to face. A reliable evaluation of this risk is the basis for the design of both specific…

The Epidemic-Type Aftershock Sequences (ETAS) model and its variants effectively capture the space-time clustering of seismicity, setting the standard for earthquake forecasting. Accurate unbiased ETAS calibration is thus crucial. But we…

Geophysics · Physics 2025-06-23 Jiawei Li , Didier Sornette , Zhongliang Wu , Jiancang Zhuang , Changsheng Jiang

Epistemic uncertainty in probabilistic seismic hazard assessment (PSHA) is commonly addressed through a logic-tree framework that combines weighted alternative models to characterize the range of plausible hazard outcomes. Implicit in this…

Geophysics · Physics 2026-03-03 Davide Zaccagnino , Didier Sornette

Extending the central concept of recurrence times for a point process to recurrent events in space-time allows us to characterize seismicity as a record breaking process using only spatiotemporal relations among events. Linking record…

Geophysics · Physics 2015-06-26 Joern Davidsen , Peter Grassberger , Maya Paczuski

Earthquakes are one of the most devastating natural disasters that plague society. A skilled, reliable earthquake forecasting remains the ultimate goal for seismologists. Using the detrended fluctuation analysis (DFA) and conditional…

The Epidemic Type Aftershock Sequence (ETAS) model is one of the most widely-used approaches to seismic forecasting. However most studies of ETAS use point estimates for the model parameters, which ignores the inherent uncertainty that…

Applications · Statistics 2021-09-14 Gordon J Ross

Geoscience and seismology have utilized the most advanced technologies and equipment to monitor seismic events globally from the past few decades. With the enormous amount of data, modern GPU-powered deep learning presents a promising…

Geophysics · Physics 2021-09-14 Bo Feng , Geoffrey C. Fox

Short-term earthquake clustering is one of the most important features of seismicity. Clusters are identified using various techniques, generally deterministic and based on spatio-temporal windowing. Conversely, the leading rail in…

Geophysics · Physics 2024-08-30 I. Spassiani , S. Gentili , R. Console , M. Murru , M. Taroni , G. Falcone

Earthquakes are commonly estimated using physical seismic stations, however, due to the installation requirements and costs of these stations, global coverage quickly becomes impractical. An efficient and lower-cost alternative is to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Daniele Rege Cambrin , Isaac Corley , Paolo Garza , Peyman Najafirad

By analyzing the seismicity in natural time and studying the evolution of the fluctuations of the entropy change of seismicity under time reversal for various scales of different length i (number of events), we can identify the approach of…

Geophysics · Physics 2025-12-30 Panayiotis A. Varotsos , Nicholas V. Sarlis , Toshiyasu Nagao

The quality of earthquake prediction is usually characterized by a two-dimensional diagram 'n' vs. 'tau', where 'n' is the rate of failures-to-predict and 'tau' is a characteristic of space- time alarm. Unlike the time prediction case, the…

Geophysics · Physics 2008-07-18 G. Molchan

Yes. Interval statistics have been used to conclude that major earthquakes are random events in time and cannot be anticipated or predicted. Machine learning is a powerful new technique that enhances our ability to understand the…