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Machine Learning and Artificial Intelligence in Geosciences de Benjamin Moseley

Machine Learning and Artificial Intelligence in Geosciences: Advances in Geophysics, cartea 61

Benjamin Moseley, Lion Krischer
en Limba Engleză Hardback – 21 sep 2020
Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various scales, a review on machine learning techniques to describe fractured media, signal augmentation to improve the generalization of deep neural networks, deep generator priors for Bayesian seismic inversion, as well as a review on homogenization for seismology, and more.


  • Provides high-level reviews of the latest innovations in geophysics
  • Written by recognized experts in the field
  • Presents an essential publication for researchers in all fields of geophysics
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Specificații

ISBN-13: 9780128216699
ISBN-10: 0128216697
Pagini: 316
Ilustrații:
  1. Preface

  2. 70 years of machine learning in geoscience in review

    3. Jesper Sören Dramsch

  3. Machine learning and fault rupture: A review

    4. Christopher X. Ren, Claudia Hulbert, Paul A. Johnson and Bertrand Rouet-Leduc

  4. Machine learning techniques for fractured media

    5. Shriram Srinivasan

  5. Seismic signal augmentation to improve generalization of deep neural networks

    6. Weiqiang Zhu , S. Mostafa Mousavi and Gregory C. Beroza

  6. Deep generator priors for Bayesian seismic inversion

    7. Zhilong Fang, Hongjian Fang and L. Demanet

  7. An introduction to the two-scale homogenization method for seismology

Yann Capdeville, Paul Cupillard and Sneha Singh


Dimensiuni: 152 x 229 mm
Greutate: 0.59 kg
Editura: ELSEVIER SCIENCE
Seria Advances in Geophysics

Public țintă

Graduate students, scientists and engineers of geophysics, physics, acoustics, civil engineering, environmental sciences, geology and planetary sciences

Cuprins

1. Preface 2. 70 years of machine learning in geoscience in review Jesper Sören Dramsch 3. Machine learning and fault rupture: A review Christopher X. Ren, Claudia Hulbert, Paul A. Johnson and Bertrand Rouet-Leduc 4. Machine learning techniques for fractured media Shriram Srinivasan 5. Seismic signal augmentation to improve generalization of deep neural networks Weiqiang Zhu , S. Mostafa Mousavi and Gregory C. Beroza 6. Deep generator priors for Bayesian seismic inversion Zhilong Fang, Hongjian Fang and L. Demanet 7. An introduction to the two-scale homogenization method for seismology Yann Capdeville, Paul Cupillard and Sneha Singh