Robotics & Machine Learning Daily News2024,Issue(Sep.3) :102-103.

Findings on Machine Learning Detailed by Investigators at University of Dayton ( Prediction of Hydrocarbons Ignition Performances Using Machine Learning Modeling )

Robotics & Machine Learning Daily News2024,Issue(Sep.3) :102-103.

Findings on Machine Learning Detailed by Investigators at University of Dayton ( Prediction of Hydrocarbons Ignition Performances Using Machine Learning Modeling )

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news reporting originatingfrom Dayton, Ohio, by NewsRx correspondents, research stated, “This study presents a computationalmethodolog y for determining the Derived Cetane Number (DCN) of practical aviation fuels. T he proposedapproach integrates a novel Quantitative Structure-Property Relation ship (QSPR) model designedto predict DCN for hydrocarbon species and mixtures w ith fuel composition analysis obtained throughTwo-Dimensional Gas Chromatograph y (GCxGC).”

Key words

Dayton/Ohio/United States/North and C entral America/Cyborgs/Emerging Technologies/Hydrocarbons/Machine Learning/Organic Chemicals/University of Dayton

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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