Predicting earthquakes, eruptions, and tsunamis with machine learning forecasting /

Bibliographic Details
Corporate Author:	IGI Global Online
Other Authors:	Mobo, Froilan D. (Editor)
Format:	eBook
Language:	English
Published:	Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : IGI Global Scientific Publishing, 2026.
Subjects:	Machine learning. Earthquake prediction. Natural disasters > Planning > Data processing. Artificial intelligence. Volcanic eruptions. Tsunamis. Apprentissage automatique. Tremblements de terre > Prévision. Intelligence artificielle. Éruptions volcaniques. artificial intelligence. volcanic eruptions. tidal waves. Aftershock Sequence Forecasting. Atmospheric Precursor Forecasting. Deep Convolutional Neural Networks. Earthquake Detection and Characterization. Earthquakes Prediction. Eruption Prediction. Geospatial Software Tools. Machine Learning (ML) Real-Time Geo-Hazard Monitoring. Time-Series Analysis. Tremor Signals. Tsunami Prediction. Volcanic Seismicity. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Preface
Chapter 1. AI Beneath the Surface: Deep Learning Techniques for Detecting and Locating Earthquakes
Chapter 2. Artificial Intelligence for Environmental Resilience: Advancing Weather Forecasting, Disaster Prediction, and Biodiversity Monitoring
Chapter 3. Big Data Challenges in Real-Time Geo-Hazard Monitoring and Prediction
Chapter 4. Comparative Analysis of Machine Learning and Time Series Models for Index Prediction: A Case Study of IGI Airport, Delhi
Using Central Pollution Control Board historical daily AQI data (2018-2024), analysis included data preprocessing, calculation of AQI, exploratory analysis, and comparative assessment using standard error measures. Based on the...
Comparative Analysis of Machine Learning and Time Series Models for Index Prediction: A Case Study of IGI Airport, Delhi
Chapter 5. Deep Convolutional Neural Networks for Enhanced Earthquake Detection and Characterization: A Focus on the Philippine West Valley Fault ("The Big One")
Chapter 6. From Seismic AI to the EMI Classroom: Project-Based ESP Curriculum Design for Disaster-Ready Professionals
Chapter 7. Fundamentals of Time-Series Analysis and Feature Engineering for Geophysical Data
Chapter 8. Machine Learning for Earthquake Prediction and Characterization: Advancing Detection, Localization, and Seismic Analysis With Deep Learning
Chapter 9. Machine Learning-Driven Classification of Volcanic Seismicity and Tremor Signals for Early Eruption Forecasting
Compilation of References
About the Contributors
Index.