首页|New Findings on Machine Learning from Sorbonne University Summarized (Applicatio n of Machine Learning To Enhance the Performance of a Two-stage, Two-temperature Ejector Cycle Driven By the Waste Heat of Exhaust Gas)
New Findings on Machine Learning from Sorbonne University Summarized (Applicatio n of Machine Learning To Enhance the Performance of a Two-stage, Two-temperature Ejector Cycle Driven By the Waste Heat of Exhaust Gas)
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NETL
NSTL
Elsevier
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting from Paris, France, by NewsRx journalist s, research stated, “This article introduces an innovative two-stage, two-temper ature ejector cycle (NTDERC) capable of simultaneously generating cooling and el ectricity. It harnesses waste heat from exhaust gases and is purposefully design ed to operate with a neutral carbon footprint.”
ParisFranceEuropeCyborgsEmerging TechnologiesMachine LearningSorbonne University
NETL
NSTL
Elsevier
