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记者从福建发回的新闻报道，研究表明：“鉴于编制滑坡清单的时间紧迫，开发可转移的滑坡敏感性模型变得越来越重要，该模型可以在没有现有数据的情况下应用于区域，本研究提出了一种基于特征的领域数据挖掘方法，以提高滑坡敏感性模型的可转移性。特别是在‘无样本’地区。本研究的资助单位包括国家自然科学基金(NSFC)、福州大学贵重仪器检测基金。
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 originating from Fujian, People’s Re public of China, by NewsRx correspondents, research stated, “Given the time-cons uming nature of compiling landslide inventories, it is increasingly important to develop transferable landslide susceptibility models that can be applied to reg ions without existing data. In this study, we propose a feature-based domain ada ptation method to improve the transferability of landslide susceptibility models , especially in ‘no sample’ areas.” Funders for this research include National Natural Science Foundation of China ( NSFC), Fuzhou University Testing Fund of Precious Apparatus.
NETL
NSTL