首页|Study Findings from University of Bordeaux Provide New Insights into Machine Lea rning (Assessment of Machine Learning Algorithms for Predicting Autoignition and Ignition Delay Time In Microscale Supercritical Water Oxidation Process)
Study Findings from University of Bordeaux Provide New Insights into Machine Lea rning (Assessment of Machine Learning Algorithms for Predicting Autoignition and Ignition Delay Time In Microscale Supercritical Water Oxidation Process)
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Elsevier
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting originating from Pessac, France, by News Rx correspondents, research stated, “With recent advancements in space technolog y, there is a need to develop technologies to ensure a sustainable environment f or human survival. Among these, treatment of human and organic waste aboard mann ed space missions is a challenging task for which supercritical water oxidation using hydrothermal flames has been proposed as a possible solution.”
PessacFranceEuropeAlgorithmsCybo rgsEmerging TechnologiesMachine LearningTechnologyUniversity of Bordeaux
NETL
NSTL
Elsevier
