摘要
由一名新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-关于机器学习的详细数据已经呈现。根据NewsRx编辑在天津的新闻报道，研究表明：“冰川-水文过程在全球水循环中是必不可少的，但复杂而又不为人所知，本研究将深层Shapley加性解释(SHAP)与长期记忆(LSTM)模型相结合，构建了描述乌鲁木齐1号冰川-水文过程的机器学习(XAI)框架。”国家自然科学基金(NSFC)、天津师范大学研究生科研创新项目、第二次青藏科学考察项目、第三次新疆科学考察项目。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting out of Tianjin, People’s Republic o f China, by NewsRx editors, research stated, “The glacio-hydrological process is essential in the global water cycle but is complex and poorly understood. In th is study, we couple the deep Shapley additive explanation (SHAP) with a long sho rt-term memory (LSTM) model to construct a machine-learning (XAI) framework that describes the glacio-hydrological process in Urumqi Glacier No. 1, China.”Funders for this research include National Natural Science Foundation of China ( NSFC), Tianjin Normal University Research Innovation Project for Postgraduate gr ant, Second Qinghai-Tibet Scientific Expedition Program, Third Xinjiang Scientif ic Expedition Program.
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