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{ "item_title" : "Machine Learning in Geohazard Risk Prediction and Assessment", "item_author" : [" Biswajeet Pradhan", "Daichao Sheng", "Xuzhen He "], "item_description" : "Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mapping presents an overview of the most recent developments in machine learning techniques that have reshaped our understanding of geo-materials and management protocols of geo-risk. The book covers a broad category of research on machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping. This is a good reference for researchers, academicians, graduate and undergraduate students, professionals, and practitioners in the field of geotechnical engineering and applied geology.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/44/323/663/0443236631_b.jpg", "price_data" : { "retail_price" : "175.00", "online_price" : "175.00", "our_price" : "175.00", "club_price" : "175.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning in Geohazard Risk Prediction and Assessment|Biswajeet Pradhan

Machine Learning in Geohazard Risk Prediction and Assessment : From Microscale Analysis to Regional Mapping

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Overview

Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mapping presents an overview of the most recent developments in machine learning techniques that have reshaped our understanding of geo-materials and management protocols of geo-risk. The book covers a broad category of research on machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping. This is a good reference for researchers, academicians, graduate and undergraduate students, professionals, and practitioners in the field of geotechnical engineering and applied geology.

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Details

  • ISBN-13: 9780443236631
  • ISBN-10: 0443236631
  • Publisher: Elsevier
  • Publish Date: July 2025
  • Dimensions: 9.2 x 7.5 x 0.8 inches
  • Shipping Weight: 1.7 pounds
  • Page Count: 376

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