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-机器学习的研究结果将在一份新报告中讨论。根据来自中华人民共和国建固的新闻报道，NewsRx记者，研究本文探讨了最适合预测的机器学习模型的发展钢与FRP(纤维增强聚合物)bars混杂增强ECC(工程)抗弯性能水泥基复合材料-混凝土组合梁。五种不同的机器学习模型，即支持向量回归(SVR)、极梯度提升(XGBoost)、多层感知器(MLP)、采用随机森林(RF)和极随机树(ERT)。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. According tonews reporting originating from Jian gsu, People’s Republic of China, by NewsRx correspondents, researchstated, “Thi s paper explores the development of the most suitable machine learning models fo r predictingthe bending capacity of steel and FRP (Fiber Reinforced Ploymer) ba rs hybrid reinforced ECC (EngineeredCementitious Composites)-concrete composite beams. Five different machine learning models, namelySupport Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), Multilayer Perceptron (MLP),Random Forest (RF), and Extremely Randomized Trees (ERT), were employed.”
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