首页|Researchers from Sun Yat-sen University Describe Findings in Machine Learning (P rediction of Two-phase Flow Patterns Based On Machine Learning)
Researchers from Sun Yat-sen University Describe Findings in Machine Learning (P rediction of Two-phase Flow Patterns Based On Machine Learning)
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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.”
ZhuhaiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesK-nearest NeighborMachine LearningPattern PredictionSun Yat-sen University
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