New Machine Learning Findings from Shanghai University Described (A Multi-object ive Optimization Based On Machine Learning for Dimension Precision of Wax Patter n In Turbine Blade Manufacturing)
New Machine Learning Findings from Shanghai University Described (A Multi-object ive Optimization Based On Machine Learning for Dimension Precision of Wax Patter n In Turbine Blade Manufacturing)
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 Shanghai, Pe ople's Republic of China, by NewsRx journalists, research stated, "Wax pattern f abrication in the investment casting of hollow turbine blades directly determine s the dimension accuracy of subsequent casting, and therefore significantly affe cts the quality of final product. In this work, we develop a machine learning-ba sed multi-objective optimization framework for improving dimension accuracy of w ax pattern by optimizing its process parameters." Financial supporters for this research include National Key Research and Develop ment Program of China, National Science and Technology Major Project "Aeroengine and Gas Turbine" of China.
Key words
Shanghai/People's Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/Shanghai University
NETL
NSTL