Robotics & Machine Learning Daily News2024,Issue(Jun.18) :11-12.

Hohai University Reports Findings in Machine Learning (Assessment of monthly run off simulations based on a physics-informed machine learning framework: The effe ct of intermediate variables in its construction)

河海大学报告了机器学习的发现(基于物理信息机器学习框架的月度运行模拟评估:中间变量在其构建中的作用)

Robotics & Machine Learning Daily News2024,Issue(Jun.18) :11-12.

Hohai University Reports Findings in Machine Learning (Assessment of monthly run off simulations based on a physics-informed machine learning framework: The effe ct of intermediate variables in its construction)

河海大学报告了机器学习的发现(基于物理信息机器学习框架的月度运行模拟评估:中间变量在其构建中的作用)

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摘要

一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报告的主题。根据《中国人民日报》南京新闻报道,NewsRx编辑的研究表明:“水文预报对于水资源管理和规划具有重要意义,特别是在洪水和干旱等极端事件日益频繁的情况下。基于Physics-Informed Machine Learning(PIML)模型有效地将概念水文模型与机器学习(ML)模型结合起来。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Nanjing, People's Repu blic of China, by NewsRx editors, research stated, "Hydrological forecasting is of great importance for water resources management and planning, especially give n the increasing occurrence of extreme events such as floods and droughts. The p hysics-informed machine learning (PIML) models effectively integrate conceptual hydrologic models with machine learning (ML) models."

Key words

Nanjing/People's Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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