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Updated: May 22, 2025

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

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基于森林的随机预测浅坡的稳定性,考虑到不和土壤水分的时空变化

Yangyang Li1,2, Saranya Rangarajan3, Yusen Cheng4

  • 1Suzhou Industrial Park Monash Research Institute of Science and Technology, Monash University, No. 1 Huayun Road, SIP Suzhou, Suzhou, 215000, PR China. yangyang.li@monash.edu.

Scientific reports
|March 14, 2025
PubMed
概括

本研究提出了一个有效的框架,将机器学习和物理模型结合起来,用于预测极端降雨下的斜坡稳定性. 新方法提高了准确性,并显著提高了对滑坡风险评估的计算效率.

关键词:
机器学习 机器学习斜坡的稳定性 斜坡的稳定性土壤水分 土壤水分不和的土壤 不和的土壤

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