Bayesian data analysis and modelling linked with machine learning offers a new tool for handling geotechnical data. This book presents recent advancements made by the author in the area of probabilistic geotechnical site characterization. Two types of correlation play central roles in geotechnical site characterization: cross-correlation among soil properties and spatial-correlation in the underground space. The book starts with the introduction of Bayesian notion of probability "degree of belief", showing that well-known ...
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Bayesian data analysis and modelling linked with machine learning offers a new tool for handling geotechnical data. This book presents recent advancements made by the author in the area of probabilistic geotechnical site characterization. Two types of correlation play central roles in geotechnical site characterization: cross-correlation among soil properties and spatial-correlation in the underground space. The book starts with the introduction of Bayesian notion of probability "degree of belief", showing that well-known probability axioms can be obtained by Boolean logic and the definition of plausibility function without the use of the notion "relative frequency". It then reviews probability theories and useful probability models for cross-correlation and spatial correlation. Methods for Bayesian parameter estimation and prediction are also presented, and the use of these methods demonstrated with geotechnical site characterization examples. Bayesian Machine Learning in Geotechnical Site Characterization suits consulting engineers and graduate students in the area.
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Add this copy of Bayesian Machine Learning in Geotechnical Site to cart. $169.06, new condition, Sold by discount_scientific_books rated 5.0 out of 5 stars, ships from Sterling Heights, MI, UNITED STATES, published 2024 by CRC Press.
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Fine. 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. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Bayesian Machine Learning in Geotechnical Site to cart. $199.03, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2024 by CRC Press.
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Fine. 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. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Bayesian Machine Learning in Geotechnical Site to cart. $213.66, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2024 by CRC Press.
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Seller's Description:
New. 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. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
