Bikash Sadhukhan

Can Artificial Intelligence Aid in Forecasting Earthquakes? (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Can Artificial Intelligence Aid in Forecasting Earthquakes? explores the potential of AI in revolutionizing earthquake forecasting and early warning systems. This book delves into the latest advancements in computational intelligence, rule-based approaches, machine learning, and deep learning algorithms. By examining the evolution of research and the current state of earthquake early warning systems, the author sheds light on the data typically used in seismic forecasting. Other significant points include an analysis of various AI techniques for earthquake prediction and early warning, a discussion on the advantages and limitations of AI-based forecasting, and future implications for the field. - Explores 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 insights into the latest advancements in seismic data analysis, helping readers navigate complexities such as interpreting seismic signals and integrating diverse datasets

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 275
• Erscheinungstermin: 1. Oktober 2025
• Englisch
• ISBN-13: 9780443383441
• Artikelnr.: 75442585

Autorenporträt

Bikash Sadhukhan is an accomplished Academician and Researcher in the field of Computer Science and Engineering. The author is currently serving as an Associate Professor at Techno International New Town, Kolkata, India.

Inhaltsangabe

1. Introduction
2. Earthquake Early Warning systems
3. Evolution of Earthquake Forecasting Research
4. Data Used in Earthquake Prediction
5. AI Techniques for Earthquake Prediction
6. Application of AI Techniques for Earthquake Forecasting
7. Advantages and Limitations of AI-Based Earthquake Prediction
8. Conclusions