This paper provides theoretical and practical arguments regarding the possibility of predicting strong and major earthquakes worldwide. Many strong and major earthquakes can be predicted at least two to five months in advance, based on identifying stressed areas that begin to behave abnormally before strong events, with the size of these areas corresponding to Dobrovolsky formula. We make predictions by combining knowledge from many different disciplines: physics, geophysics, seismology, geology, and earth science, among others. An integrated approach is used to identify anomalies and make predictions, including satellite remote sensing techniques and data from ground-based instruments. Terabytes of information are currently processed every day with many different multi-parametric prediction systems applied thereto. Alerts are issued if anomalies are confirmed by a few different systems. It has been found that geophysical patterns of earthquake preparation and stress accumulation are similar for all key seismic regions. The same earthquake prediction methodologies and systems have been successfully applied in global practice since 2013, with the technology successfully used to retrospectively test against more than 700 strong and major earthquakes since 1970.
How to quantify earthquake predictability? Advances in earthquake forecasting and predictability limits
The Institute of Statistical Mathematics（统计数学研究所）；the Graduate University for Adavanced Studies (SOKENDai)（advanced studies 研究生院（SOKENDai））；Institute of Risk Analysis, Prediction and Management, Southern University of Science and Technology（南方科技大学风险分析、预测与管理研究院）
The Andravida, Greece EQ (8/06/2008, Ms=7.0R). An "a posteriori" analysis for the determination of its location, occurrence time and magnitude parameters in terms of short-term predictability
Text Classification of the Precursory Accelerating Seismicity Corpus: Inference on some Theoretical Trends in Earthquake Predictability Research from 1988 to 2018
Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting
University of Virginia（弗吉尼亚大学）；University of California, Davis（加州大学戴维斯分校）；Santa Fe Institute（圣达菲研究所）；Jet Propulsion Laboratory（喷气推进实验室）；California Institute of Technology（加州理工学院）；University of California, Irvine（加州大学欧文分校）
本章首先提出了一个相当个人的看法，一些不同方面的可预测性，从简单的线性系统到高维非线性系统与随机强迫，表现出突发的性质，如相变和政权转移渐强。然后，地震，金融崩溃和癫痫发作的现象之间的详细对应关系。所提供的统计证据提供了一般相图的实质内容，用于理解这些系统时空组织的许多方面。一个关键的见解是组织的证据和机制方面的两个总结措施：（i）的幅度的混乱或异质性的系统和（ii）耦合或相互作用的强度在系统的组件。最近确定的地震和癫痫发作之间的显着对应关系的基础上，我们提出了详细的信息一类随机点过程，已被发现是特别强大的描述地震现象，我们认为，在癫痫学有一个很好的未来。所谓的自激霍克斯点过程（self-exciting Hawkes point processes）简单地描述了事件可以触发其他事件的想法，它们之间的级联相互作用和相互影响对于理解这些系统的行为至关重要。
