Computation, Optimization, and Machine Learning in Seismology (AGU Advanced Textbooks) - Tapa blanda

Libro 8 de 8: AGU Advanced Textbooks

Mallick, Subhashis

 
9781119654469: Computation, Optimization, and Machine Learning in Seismology (AGU Advanced Textbooks)
Tapa blanda
ISBN 10: 1119654467 ISBN 13: 9781119654469
Editorial: American Geophysical Union, 2025

Sinopsis

A textbook applying fundamental seismology theories to the latest computational tools

The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances in computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models.

Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data.

Volume highlights include:

  • Mathematical foundations and key equations for computational seismology
  • Essential theories, including wave propagation and elastic wave theory
  • Processing, mapping, and interpretation of prestack data
  • Model-based optimization and artificial intelligence methods
  • Applications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problems
  • Exercises applying the main concepts of each chapter

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Subhashis Mallick, University of Wyoming, USA

De la contraportada

Computation, Optimization, and Machine Learning in Seismology

The goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these models with observations to identify subsurface rock properties. With recent advances in computing technology, including machine learning, it is now possible to automate matching procedures and use waveform inversion or optimization to create large-scale models.

Computation, Optimization, and Machine Learning in Seismology provides students with a detailed understanding of seismic wave theory, optimization theory, and how to use machine learning to interpret seismic data.

Volume highlights include:

  • Mathematical foundations and key equations for computational seismology
  • Essential theories, including wave propagation and elastic wave theory
  • Processing, mapping, and interpretation of prestack data
  • Model-based optimization and artificial intelligence methods
  • Applications for earthquakes, exploration seismology, depth imaging, and multi-objective geophysics problems
  • Exercises applying the main concepts of each chapter

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
American Geophysical Union
Año de publicación
2025
Idioma
Inglés
ISBN 10 
1119654467
ISBN 13 
9781119654469
Encuadernación
Tapa blanda
Número de páginas
416
Contacto del fabricante
American Geophysical Union
https://www.agu.org/

2000 Florida Avenue, N.W.
Washington
DC
20009
Estados Unidos de America
Persona responsable
no disponible