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-调查人员讨论人工智能的新发现。根据来自…的消息Kumoh国家技术研究所由NewsRx记者报道，“在这项研究中，”评价了机器学习(ML)算法预测颗粒物浓度（PM10和PM2.5）利用中小城市空气质量和气象资料。ML模型，包括多元线性回归(MLR)、决策树回归(DTR)、随机森林(RF)、极值利用梯度升压(XGB)、Lig-ht梯度升压机(LGB)对PM10进行了预测和PM2.5个启示。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Investigators discuss new findings in artificial intelligence. According to news originating fromthe Kumoh National Institute of Technology by NewsRx correspondents, research stated, “In this study,Machine L earning (ML) algorithms were evaluated to predict the concentration of particula te matter(PM10 and PM2.5) using air quality and meteorological data in small/me dium-sized city. ML models,including Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest (RF), ExtremeGradient Boosting (XGB), Lig ht Gradient Boosting Machine (LGB), were used to predict PM10and PM2.5 concentr ations.”
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