Can Artificial Intelligence Aid in Forecasting Earthquakes? poses a fascinating question about the applicability of artificial intelligence (AI) in earthquake forecasting and early warning systems. The author comprehensively reviews the latest advancements in computational intelligence, rule-based approaches, machine learning, and deep learning algorithms used in seismic signal analysis. The opening chapters thoroughly examine the evolution of earthquake forecasting research and the current state of earthquake early warning systems. After a close look at what data is most often used in earthquake forecasting, the author explores the various AI techniques that have the potential for application in earthquake prediction, forecasting, and early warning systems. This is followed by a rigorous discussion of the advantages and limitations of AI-based earthquake forecasting as well as future implications for the field. Given the increasing frequency and impact of seismic events globally, researchers will appreciate this cutting-edge resource on the expanding role of AI in seismic forecasting.

• Explores the innovative advancements in artificial intelligence for earthquake forecasting and prediction and how these techniques, especially deep learning algorithms, could eventually outperform other methods
• Compares various AI methods, including computational intelligence, rule-based approaches, machine learning, and deep learning algorithms
• Offers insight into the latest advancements in seismic data analysis, helping readers navigate complexities such as interpreting seismic signals and integrating diverse datasets