首页|Reports on Machine Learning from Fuzhou University Provide New Insights (Real-ti me Prediction of Pool Fire Burning Rates Under Complex Heat Transfer Effects Inf luenced By Ullage Height: a Comparative Study of Bpnn and Svr)
Reports on Machine Learning from Fuzhou University Provide New Insights (Real-ti me Prediction of Pool Fire Burning Rates Under Complex Heat Transfer Effects Inf luenced By Ullage Height: a Comparative Study of Bpnn and Svr)
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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 out of Fuzhou, People ’s Republic of China, by NewsRx editors, research stated, “Thisresearch utilize s machine learning methods to forecast the complex, non-linear thermal phenomena , alongwith heat transfer mechanisms, that influence the burning rate of pool f ires, especially with changes inullage height. Experiments involving pool fires were systematically designed and carried out, incorporatingdifferent diameters and ullage heights.”
FuzhouPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningFuzhou University
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