Machine Learning and Artificial Intelligence in Geosciences
Specificaties
Gebonden, blz.
|
Engels
Elsevier Science |
e druk, 2020
ISBN13: 9780128216699
Rubricering
Onderdeel van serie
Advances in Geophysics
Levertijd ongeveer 8 werkdagen
Samenvatting
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.
Specificaties
ISBN13:9780128216699
Taal:Engels
Bindwijze:Gebonden
Uitgever:Elsevier Science
Serie:Advances in Geophysics
Inhoudsopgave
<p>1. Preface<br>2. 70 years of machine learning in geoscience in review<br>Jesper Sören Dramsch<br>3. Machine learning and fault rupture: A review<br>Christopher X. Ren, Claudia Hulbert, Paul A. Johnson and Bertrand Rouet-Leduc<br>4. Machine learning techniques for fractured media<br>Shriram Srinivasan<br>5. Seismic signal augmentation to improve generalization of deep neural networks<br>Weiqiang Zhu , S. Mostafa Mousavi and Gregory C. Beroza<br>6. Deep generator priors for Bayesian seismic inversion<br>Zhilong Fang, Hongjian Fang and L. Demanet<br>7. An introduction to the two-scale homogenization method for seismology<br>Yann Capdeville, Paul Cupillard and Sneha Singh</p>