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新报告。根据消息来源在中华人民共和国济南，由NewsRx记者报道，研究表明，“动态弹性”路基土模量(MR)是评价路基土动力承载能力和承载能力的基本参数路基填料和结构的使用回弹力，以及用于计算路基填料和结构的使用回弹力的仪器输入路面结构的力学响应与疲劳寿命。准确合理地描述利用支持向量机建立了土壤的MR、机器学习(ML)模型，随机森林和极端梯度boosting算法基于lar ge尺度的3533数据集在路基土壤上进行的MR试验记录。 ”
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 originatingfrom Jinan, People’s Republic of C hina, by NewsRx correspondents, research stated, “The dynamic resilientmodulus (MR) of a subgrade soil is a fundamental parameter for evaluating the dynamic st ability andservice resilience of subgrade fillers and structures, as well as an instrumental input for calculating themechanical response and fatigue life of a pavement structure. To accurately and reasonably characterisethe MR of subgra de soils, machine learning (ML) models were established using the support vector machine,random forest, and extreme gradient boosting algorithms based on a lar ge-scale dataset including 3533records of MR tests conducted on subgrade soils. ”
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