首页|New Machine Learning Study Findings Recently Were Published by a Researcher at Hohai University (Intelligent optimization of axialflow pump using physics-considering machine learning)
New Machine Learning Study Findings Recently Were Published by a Researcher at Hohai University (Intelligent optimization of axialflow pump using physics-considering machine learning)
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-New research on artificial intelligence is the subject of a new report. According to news reporting originating from Nanjing, People's Republic of China, by NewsRx correspondents, research stated, "To address the significant energy waste generated by axial flow pumps, this paper proposes an intelligent optimization method based on physics-considering machine learning." The news reporters obtained a quote from the research from Hohai University: "First, a highly parameterized geometric design theory is constructed using six featured variables to achieve a complete three-dimensional modeling of the blade geometry. Four hundred preliminary cases are studied using the computational fluid dynamics (CFD) method with various combinations of these featured variables to obtain a preliminary solution. The best preliminary design has an efficiency of 83.33%, and a head of 5.495 m. To further improve this performance, this paper also presents a high-precision prediction model for the energy performance of axial flow pump based on BPNN and the Encoding Layers of RandLA-Net created. Afterwards, a multi-population genetic algorithm is used to quickly find the optimal solution within the prediction mode range. The algorithm achieved a highest efficiency of 86.373% and was validated by numerical simulation with a value of 86.057% and a prediction error of 0.316%."
Hohai UniversityNanjingPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
