Bayesian Compressive Sensing for Site Characterization
eBook - ePub

Bayesian Compressive Sensing for Site Characterization

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Bayesian Compressive Sensing for Site Characterization

About this book

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 tested. 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.

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Yes, you can access Bayesian Compressive Sensing for Site Characterization by Yu Wang,Tengyuan Zhao,Yue Hu,Zheng Guan,Kok-Kwang Phoon in PDF and/or ePUB format, as well as other popular books in Computer Science & Data Mining. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2025
eBook ISBN
9781040734834
Topic
Computer Science
Subtopic
Data Mining
Index
Computer Science

Table of contents

  1. Cover
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication
  7. Table of Contents
  8. Foreword
  9. Preface
  10. Acknowledgments
  11. About the Authors
  12. 1 Introduction
  13. 2 Compressive Sensing (CS)
  14. 3 Analytics of Sparse Measurements on Spatial Data by Bayesian Compressive Sensing (BCS)
  15. 4 Simulation of Spatial Data from Sparse Measurements
  16. 5 Sample Size Determination for Site Characterization
  17. 6 Adaptive Sampling in Site Characterization
  18. 7 Software ASSD-BCS
  19. 8 Summaries and Additional Remarks
  20. Index