Can Artificial Intelligence Aid in Forecasting Earthquakes?
- 1st Edition - October 1, 2025
- Author: Bikash Sadhukhan
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 8 3 4 3 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 8 3 4 4 - 1
Can Artificial Intelligence Aid in Forecasting Earthquakes? explores the potential of AI in revolutionizing earthquake forecasting and early warning systems. This book delves… Read more
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
Primarily researchers and academics involved in the fields of geophysics, seismology, and data science
1: Introduction
1.1 Formation of Earthquakes
1.2 Seismic precursors
1.3 Nonseismic precursors
1.4 Complexity, Chaos and Predictability of Earthquakes
1.5 Earthquake Science
1.6 Earthquake forecasting methods
1.7 Role of artificial intelligence in earthquake forecasting
2: Earthquake Early Warning systems
2.1 Introduction to Earthquake Early Warning Systems
2.2 Technologies and Methodologies for Earthquake Early Warning
2.3 Case Studies of Effective Early Warning Systems
2.4 Role of Artificial Intelligence in Earthquake Early Warning
3: Evolution of Earthquake Forecasting Research
3.1 Research Based on Earthquake Precursors
3.2 Research Based on Historical Seismic Data Analysis
4: Data Used in Earthquake Prediction
4.1 Seismic data
4.2 GPS data
4.3 Satellite Imagery
4.4 Distributed Acoustic Sensing Technology
4.5 Other types of data
5: AI Techniques for Earthquake Prediction
5.1 Computational intelligence-based approach
5.2 Rule-based approaches
5.3 Machine learning approaches
5.4 Deep learning approaches
5.5 Explainable Artificial Intelligence
5.6 Generative AI
6: Application of AI Techniques for Earthquake Forecasting
6.1 Computational intelligence-based approach
6.2 Rule-based approaches
6.3 Machine learning approaches
6.4 Deep learning approaches
6.5 Explainable Artificial Intelligence
6.6 Generative AI
7: Advantages and Limitations of AI-Based Earthquake Prediction
7.1 Advantages of AI-based earthquake prediction
7.2 Limitations of AI-based earthquake prediction
7.3 Challenges and Future Directions
8: Conclusions
1.1 Formation of Earthquakes
1.2 Seismic precursors
1.3 Nonseismic precursors
1.4 Complexity, Chaos and Predictability of Earthquakes
1.5 Earthquake Science
1.6 Earthquake forecasting methods
1.7 Role of artificial intelligence in earthquake forecasting
2: Earthquake Early Warning systems
2.1 Introduction to Earthquake Early Warning Systems
2.2 Technologies and Methodologies for Earthquake Early Warning
2.3 Case Studies of Effective Early Warning Systems
2.4 Role of Artificial Intelligence in Earthquake Early Warning
3: Evolution of Earthquake Forecasting Research
3.1 Research Based on Earthquake Precursors
3.2 Research Based on Historical Seismic Data Analysis
4: Data Used in Earthquake Prediction
4.1 Seismic data
4.2 GPS data
4.3 Satellite Imagery
4.4 Distributed Acoustic Sensing Technology
4.5 Other types of data
5: AI Techniques for Earthquake Prediction
5.1 Computational intelligence-based approach
5.2 Rule-based approaches
5.3 Machine learning approaches
5.4 Deep learning approaches
5.5 Explainable Artificial Intelligence
5.6 Generative AI
6: Application of AI Techniques for Earthquake Forecasting
6.1 Computational intelligence-based approach
6.2 Rule-based approaches
6.3 Machine learning approaches
6.4 Deep learning approaches
6.5 Explainable Artificial Intelligence
6.6 Generative AI
7: Advantages and Limitations of AI-Based Earthquake Prediction
7.1 Advantages of AI-based earthquake prediction
7.2 Limitations of AI-based earthquake prediction
7.3 Challenges and Future Directions
8: Conclusions
- Edition: 1
- Published: October 1, 2025
- Language: English
BS
Bikash Sadhukhan
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.
Affiliations and expertise
Associate Professor in the Department of Computer Science and Engineering at Techno International New Town, Kolkata, West Bengal, India