Robotics & Machine Learning Daily News2024,Issue(Dec.4) :51-52.

Studies from Natural Resources Canada Yield New Information about Machine Learni ng (Machine Learning Modeling for Predicting Tensile Strain Capacity of Pipeline s and Identifying Key Factors)

加拿大自然资源部的研究提供了机器学习的新信息(预测管道拉伸应变能力和识别关键因素的机器学习模型)

Robotics & Machine Learning Daily News2024,Issue(Dec.4) :51-52.

Studies from Natural Resources Canada Yield New Information about Machine Learni ng (Machine Learning Modeling for Predicting Tensile Strain Capacity of Pipeline s and Identifying Key Factors)

加拿大自然资源部的研究提供了机器学习的新信息(预测管道拉伸应变能力和识别关键因素的机器学习模型)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的最新研究结果已经发表。根据NewsRx编辑的新闻报道来自阿纳达州卡尔加里,研究称,“机器”学习(ML)技术最近在许多工程领域获得了极大的关注,包括管道材料。然而,它们在拉应变capacity(TSC)模型中的应用仍然存在未探索的。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According tonews reporting originating from Calgary, C anada, by NewsRx editors, the research stated, “Machinelearning (ML) techniques have recently gained great attention across a multitude of engineering domains,including pipeline materials. However, their application to tensile strain capa city (TSC) modeling remainsunexplored.”

Key words

Calgary/Canada/North and Central Ameri ca/Cyborgs/Emerging Technologies/Machine Learning/Natural Resources Canada

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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