摘要
由一名新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-一项关于机器学习的新研究现在已经可用。据NewsRx记者从珠海发回的新闻报道，研究表明：“小型模块堆(SMR)以其微型化、安全性和经济性等优点，已成为核能领域的研究热点，气液两相流是SMR研究和开发中最常见的现象之一。”新闻记者引用了中山大学的一篇研究文章:“一个有效的、高精度的两相流型预测模型是至关重要的,因为它将影响到热工水力和传热现象,进而影响到SMR的安全性。”选取随机森林(RF)算法和k-近邻(KNN)算法作为机器学习(ML)模型的候选算法，选取12个数据库对ML模型进行训练和测试。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting originating in Zhuhai, People’s Republic of China, by NewsRx journalists, research stated, “Due to the advantages of fle xibility, security and economy, small modular reactor (SMR) has become a researc h hotspot in the field of nuclear energy. Gas liquid two-phase flow is one of th e most common phenomena for the research and development of SMR.” The news reporters obtained a quote from the research from Sun Yat-sen Universit y, “An effective two-phase flow pattern prediction model with high accuracy is v ery crucial since it will impact the thermalhydraulic and heat transfer phenome na, and consequently, the safety of SMR. In this paper, support vector machine ( SVM), Random Forest (RF) and K-Nearest Neighbor (KNN) algorithm were chosen as t he candidates of machine learning (ML) models. we selected 12 databases to train and test ML models.”
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