首页|Researchers at Texas A&M University Release New Data on Machine Lea rning (Traditional Machine Learning Methods In Predicting the Physics of Subcrit ical Systems In Source-equilibrium)
Researchers at Texas A&M University Release New Data on Machine Lea rning (Traditional Machine Learning Methods In Predicting the Physics of Subcrit ical Systems In Source-equilibrium)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating from College Station, Texas, by NewsRx correspondents, research stated, "Reactivity measurement method s, that are formulas relating integral physics quantity to system observable, we re mostly derived from Point Reactor Kinetics (PRK). PRK presupposes fundamental mode that is driven solely by fissions; however, in Subcritical Assemblies (SCA s), an independent source is present to maintain flux." Financial support for this research came from Department of Science and Technolo gy (DOST) - Science Education Institute of the Republic of the Philippines.
College StationTexasUnited StatesN orth and Central AmericaCyborgsEmerging TechnologiesMachine LearningTexa s A&M University
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