首页|Studies from North China Electric Power University Update Current Data on Machin e Learning (A Tree-based Automated Machine Learning Approach of the Obstructed View Factor of Thermal Radiation In Nuclear Pebble Beds)
Studies from North China Electric Power University Update Current Data on Machin e Learning (A Tree-based Automated Machine Learning Approach of the Obstructed View Factor of Thermal Radiation In Nuclear Pebble Beds)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “For the nuclear p ebble bed of the high temperature gas-cooled reactor (HTGR), a tree-based automa ted machine learning approach is developed to discuss the complicated thermal ra diation behaviors. The AutoML model for calculating the obstructed view factor b etween any two particles in the pebble bed includes the gradient boosting regres sion tree model with the fine-tuned hyperparameters and the analytical base mode l.”
BeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNorth China Electric Power University
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