Machine Learning and Artificial Intelligence in Geosciences
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...
Leider schon ausverkauft
252.99 €
versandkostenfrei
126 DeutschlandCard Punkte
sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
- Ratenzahlung möglich
Produktdetails
Produktinformationen zu „Machine Learning and Artificial Intelligence in Geosciences “
Weitere Produktinformationen zu „Machine Learning and Artificial Intelligence in Geosciences “
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.
Bibliographische Angaben
- Herausgegeben:Moseley, Benjamin; Krischer, Lion
- Verlag: Academic Press
- EAN: 9780128216699
Autoren-Porträt
Ben Moseley works at the Department of Computer Science at the University of Oxford and is currently researching the use of machine learning for seismic simulation and inversion, as well as machine learning for space science. Previously he was a geophysicist in the hydrocarbon industry, with experience in seismic processing, imaging and explorationLion Krischer works at the Department of Earth Sciences at the ETH Zurich in Switzerland. His works sits at the crossroads where seismology meets computational science, Big Data engineering, and machine learning.
Inhaltsverzeichnis zu „Machine Learning and Artificial Intelligence in Geosciences “
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
Kommentar zu "Machine Learning and Artificial Intelligence in Geosciences"
0 Gebrauchte Artikel zu „Machine Learning and Artificial Intelligence in Geosciences“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Machine Learning and Artificial Intelligence in Geosciences".
Kommentar verfassen