Robotics & Machine Learning Daily News2024,Issue(Jul.2) :109-110.

Findings on Machine Learning Reported by Investigators at China University of Ge osciences (Refined Landslide Susceptibility Mapping In Township Area Using Ensem ble Machine Learning Method Under Dataset Replenishment Strategy)

中国通用科学大学研究员报告的机器学习研究结果(数据集补充策略下基于集合机器学习方法的乡镇滑坡易感性精细制图)

Robotics & Machine Learning Daily News2024,Issue(Jul.2) :109-110.

Findings on Machine Learning Reported by Investigators at China University of Ge osciences (Refined Landslide Susceptibility Mapping In Township Area Using Ensem ble Machine Learning Method Under Dataset Replenishment Strategy)

中国通用科学大学研究员报告的机器学习研究结果(数据集补充策略下基于集合机器学习方法的乡镇滑坡易感性精细制图)

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摘要

由一名新闻记者兼机器人与机器学习的新闻编辑每日新闻-调查人员发布了关于马学习的新报告。根据NewsRx编辑在中华人民共和国武汉的新闻报道,研究表明:“滑坡易感性图(LSM)作为应对全球滑坡不断增加的风险评估和预防的先决条件,值得引起相当大的关注。然而,在乡镇规模上完善的LSM仍然面临着滑坡数量有限和对与不同滑坡类型相关的相关因素的监督的问题。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting out of Wuhan, People’s Republic of C hina, by NewsRx editors, research stated, “Landslide susceptibility mapping (LSM ) warrants considerable attention as a prerequisite for risk assessment and prev ention in response to the increasing global occurrences of landslides. However, refined LSM at the township scale still faces the problem of the limited number of landslides and the oversight of relevant factors associated with different la ndslide types.”

Key words

Wuhan/People's Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/China University of Geoscienc es

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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