9781032458090 - bayesian compressive sensing for site characterization di wang, yu; zhao, tengyuan; hu, yue; guan, zheng; phoon, kok-kwang (18 risultati)
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Bayesian Compressive Sensing for Site Characterization (Challenges in Geotechnical and Rock Engineering)
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization (Challenges in Geotechnical and Rock Engineering)
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization (Challenges in Geotechnical and Rock Engineering)
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization (Challenges in Geotechnical and Rock Engineering)
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization
Wang, Yu; Zhao, Tengyuan; Hu, Yue; Guan, Zheng; Phoon, Kok-Kwang
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Bayesian Compressive Sensing for Site Characterization
Wang, Yu/ Zhao, Tengyuan/ Hu, Yue/ Guan, Zheng/ Phoon, Kok-Kwang
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 256 pages. 9.19x6.13x9.21 inches. In Stock.
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Hardcover. Condizione: new. Hardcover. Site characterization is indispensable to good geotechnical or rock engineering practice as every site is unique, but technical, budget, time, or access constraints typically result in only a tiny fraction of the underground soil and rock in a site being visually inspected, sampled, or test…ed. This leads to a long- lasting challenge of sparse measurements in geo- sciences and engineering. This book introduces Bayesian compressive sensing or sampling (BCS) as a highly efficient spatial data analytic and simulation method for the efficient modelling of spatial geo- data from sparse measurements, with quantified reliability and uncertainty to further optimize site characterization. It provides the necessary theory and computational tools for setting up and solving a sparse spatial data modeling problem using BCS. This book suits graduate students, academics, researchers, and engineers interested in site characterization from sparse measurements in geotechnical and rock engineering, and also those modeling other spatially varying phenomena such as air quality data, soil or water pollution data, and meteorological data. This is supplemented with a software called Analytics of Sparse Spatial Data using Bayesian compressive sampling/ sensing and illustrative examples, and enables hands- on experience of spatial data analytics and simulation using sparse measurements. Bayesian compressive sensing/sampling is a very efficient analytic and simulation method for modelling spatial geo-data from sparse measurements, to quantify reliability and uncertainty, and to optimize site characterization. This provides principles with software for graduate students, and geotechnical or environmental engineers. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Hardcover. Condizione: new. Hardcover. Site characterization is indispensable to good geotechnical or rock engineering practice as every site is unique, but technical, budget, time, or access constraints typically result in only a tiny fraction of the underground soil and rock in a site being visually inspected, sampled, or test…ed. This leads to a long- lasting challenge of sparse measurements in geo- sciences and engineering. This book introduces Bayesian compressive sensing or sampling (BCS) as a highly efficient spatial data analytic and simulation method for the efficient modelling of spatial geo- data from sparse measurements, with quantified reliability and uncertainty to further optimize site characterization. It provides the necessary theory and computational tools for setting up and solving a sparse spatial data modeling problem using BCS. This book suits graduate students, academics, researchers, and engineers interested in site characterization from sparse measurements in geotechnical and rock engineering, and also those modeling other spatially varying phenomena such as air quality data, soil or water pollution data, and meteorological data. This is supplemented with a software called Analytics of Sparse Spatial Data using Bayesian compressive sampling/ sensing and illustrative examples, and enables hands- on experience of spatial data analytics and simulation using sparse measurements. Bayesian compressive sensing/sampling is a very efficient analytic and simulation method for modelling spatial geo-data from sparse measurements, to quantify reliability and uncertainty, and to optimize site characterization. This provides principles with software for graduate students, and geotechnical or environmental engineers. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Hardcover. Condizione: new. Hardcover. Site characterization is indispensable to good geotechnical or rock engineering practice as every site is unique, but technical, budget, time, or access constraints typically result in only a tiny fraction of the underground soil and rock in a site being visually inspected, sampled, or test…ed. This leads to a long- lasting challenge of sparse measurements in geo- sciences and engineering. This book introduces Bayesian compressive sensing or sampling (BCS) as a highly efficient spatial data analytic and simulation method for the efficient modelling of spatial geo- data from sparse measurements, with quantified reliability and uncertainty to further optimize site characterization. It provides the necessary theory and computational tools for setting up and solving a sparse spatial data modeling problem using BCS. This book suits graduate students, academics, researchers, and engineers interested in site characterization from sparse measurements in geotechnical and rock engineering, and also those modeling other spatially varying phenomena such as air quality data, soil or water pollution data, and meteorological data. This is supplemented with a software called Analytics of Sparse Spatial Data using Bayesian compressive sampling/ sensing and illustrative examples, and enables hands- on experience of spatial data analytics and simulation using sparse measurements. Bayesian compressive sensing/sampling is a very efficient analytic and simulation method for modelling spatial geo-data from sparse measurements, to quantify reliability and uncertainty, and to optimize site characterization. This provides principles with software for graduate students, and geotechnical or environmental engineers. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Buch. Condizione: Neu. Bayesian Compressive Sensing for Site Characterization | Yu Wang (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2025 | CRC Press | EAN 9781032458090 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
