Investigators at Bulgarian Academy of Sciences Describe Findings in Machine Lear ning (A Novel Approach To Predict the Effect of Chemical Composition and Thermo- mechanical Processing Parameters On Cu-ni-si Alloys Using a Hybrid Deep Learning and ...)
Investigators at Bulgarian Academy of Sciences Describe Findings in Machine Lear ning (A Novel Approach To Predict the Effect of Chemical Composition and Thermo- mechanical Processing Parameters On Cu-ni-si Alloys Using a Hybrid Deep Learning and ...)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating in Sofia, Bulga ria, by NewsRx editors, the research stated, “The study presents a novel hybrid deep learning and ensemble learning (DL-EL) model to predict the effects of chem ical composition and thermo-mechanical processing on the properties of Cu-Ni-Si alloys. The model integrates various input parameters like chemical composition and thermo-mechanical processing parameters and aims to predict key output prope rties such as mechanical properties and electrical conductivity.” Financial support for this research came from National Science Fund of Bulgaria.
Key words
Sofia/Bulgaria/Europe/Alloys/Cyborgs/Emerging Technologies/Machine Learning/Bulgarian Academy of Sciences
NETL
NSTL