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-调查人员发布马学习的新报告。根据新闻报道在印度新德里，NewsRx e Ditors的研究表明，“最近，高熵合金(HEAs)”由于其广阔的设计空间和显著的性能，使其具有广阔的性能，因而被广泛应用各种成分的可能组合的变化。本研究利用机器学习技术，包括随机函数(RF)、k近邻(KNN)、XGBoost(XGB)、Decision树(DT)和支持向量回归器(SVR)预测二元流体的流变应力行为FC C相CoCrCu1.2FeNi高熵合金(HEA)在新温度和应变下的还原实验依赖性。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingout of New Delhi, India, by NewsRx e ditors, research stated, “In recent time, high entropy alloys (HEAs)are widely used due to their wide design space and remarkable properties allowing a vast ra nge of propertyvariations with myriads of possible combinations of constituent elements. This research utilizes machinelearning techniques, including Random F orest (RF), K-Nearest Neighbors (KNN), XGBoost (XGB), DecisionTree (DT), and Su pport Vector Regressor (SVR), to predict the flow stress behavior of the dualFC C phase CoCrCu1.2FeNi high entropy alloy (HEA) at new temperature and strain rat es to reduce theexperiments dependency.”
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