This presents recent advancements in probabilistic geotechnical site characterization. It reviews probability theories and models for cross correlation and spatial correlation, and presents methods for Bayesian parameter estimation and prediction. Use of these methods is demonstrated with geotechnical site characterization examples.
Read More
This presents recent advancements in probabilistic geotechnical site characterization. It reviews probability theories and models for cross correlation and spatial correlation, and presents methods for Bayesian parameter estimation and prediction. Use of these methods is demonstrated with geotechnical site characterization examples.
Read Less
Add this copy of Bayesian Machine Learning in Geotechnical Site to cart. $206.67, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2024 by CRC Press.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Print on demand Sewn binding. Cloth over boards. 176 p. Contains: Unspecified, Illustrations, black & white, Line drawings, black & white, Tables, black & white. Challenges in Geotechnical and Rock Engineering.
