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Updated: Jun 27, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

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在小样本场景下评估森林火灾易感性:使用传导支矢量机器进行半监督学习方法.

Tianwu Ma1, Gang Wang2, Rui Guo3

  • 1Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China; School of Geography, Nanjing Normal University, Nanjing, 210023, China.

Journal of environmental management
|April 27, 2024
PubMed
概括

半监督学习,使用传导支持矢量机器 (TSVM),在数据有限的情况下,与传统的监督方法相比,提供更高的森林火灾易感性评估准确性. 这种方法对于有效的环境管理和公共安全至关重要.

关键词:
森林大火 森林大火一个有限的样本.半监督学习 半监督学习空间预测的空间预测监督学习学习 监督学习没有标记的数据.

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