Robotics & Machine Learning Daily News2024,Issue(Nov.29) :65-66.

Study Data from Taiyuan University of Science & Technology Update Knowledge of Machine Learning (Performance Prediction of 304 L Stainless Steel B ased On Machine Learning)

太原理工大学学习数据更新机器学习知识(基于机器学习的304l不锈钢性能预测)

Robotics & Machine Learning Daily News2024,Issue(Nov.29) :65-66.

Study Data from Taiyuan University of Science & Technology Update Knowledge of Machine Learning (Performance Prediction of 304 L Stainless Steel B ased On Machine Learning)

太原理工大学学习数据更新机器学习知识(基于机器学习的304l不锈钢性能预测)

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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新闻-机器学习的新研究是一份报告的主题。根据新闻报道来自中国人民共和国太原,由NewsRx记者报道,研究称,“与”随着测试技术和数据挖掘方法的发展,机器学习(ML)已经开始广泛应用于包括不锈钢在内的各种体系材料性能的预测改进性能。解决传统实验和统计方法的局限性在预测材料热变形的基础上,建立了基于预测机器学习的材料热变形预测模型根据热模拟压缩试验获得的数据。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning is the subject o f a report. According to news reportingoriginating from Taiyuan, People’s Repub lic of China, by NewsRx correspondents, research stated, “Withthe development o f testing technology and data mining methodologies, machine learning (ML) has be enwidely applied for predicting the performance of materials in various systems including stainless steel withimproved performance. To address the limitations of traditional experimental and statistical methods inpredicting the thermal d eformation of materials, a predictive machine learning model was developed basedon the data obtained from thermal simulation compression tests.”

Key words

Taiyuan/People’s Republic of China/Asi a/Algorithms/Cyborgs/Emerging Technologies/Machine Learning/Stainless Steel/Taiyuan University of Science & Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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