首页|Investigators from Jilin University Have Reported New Data on Machine Learning ( Prediction of the Swelling Rate of Irradiated Type 316 Stainless Steels Via Mach ine Learning Methods)
Investigators from Jilin University Have Reported New Data on Machine Learning ( Prediction of the Swelling Rate of Irradiated Type 316 Stainless Steels Via Mach ine Learning Methods)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning.According to news originating from Changchun, People’s Republic of China, by NewsRx correspondents, research stated, “Irradiationinduced void s welling typically leads to the degradation of mechanical properties of metals an d the significant decrease in material density, which influences the safety of n uclear reactors.It is essential to understand the irradiation-induced swelling behavior of alloys.”
ChangchunPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningStainless SteelJilin Un iversity
NETL
NSTL
