首页|Reports Summarize Machine Learning Findings from King Mongkut’s Institute of Tec hnology (Machine Learning Based Prediction and Iso-conversional Assessment of Ox idatively Torrefied Spent Coffee Grounds Pyrolysis)
Reports Summarize Machine Learning Findings from King Mongkut’s Institute of Tec hnology (Machine Learning Based Prediction and Iso-conversional Assessment of Ox idatively Torrefied Spent Coffee Grounds Pyrolysis)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news reportingout of Bangkok, Thailand, by NewsRx editors, research stated, “This research focused on developing apredictive mode l for mass loss during the pyrolysis of oxidatively torrefied spent coffee groun ds (SCG)using machine learning techniques. Four algorithms were employed: artif icial neural networks (ANN), knearestneighbors (k-NN), random forest (RF), and decision tree (DT), with the RF model demonstratingsuperior performance (R-2 > 0.9981, RMSE <1.346) for both training and testing sets.”
BangkokThailandAsiaCyborgsEmergi ng TechnologiesMachine LearningKing Mongkut’s Institute of Technology
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