首页|Reports from Silesian University of Technology Highlight Recent Findings in Mach ine Learning (Piezotensornet: Crystallography Informed Multi-scale Hierarchical Machine Learning Model for Rapid Piezoelectric Performance Finetuning)
Reports from Silesian University of Technology Highlight Recent Findings in Mach ine Learning (Piezotensornet: Crystallography Informed Multi-scale Hierarchical Machine Learning Model for Rapid Piezoelectric Performance Finetuning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting out of Gliwice, Poland, by N ewsRx editors, research stated, “Piezoelectric devices offer numerous opportunit ies for sustainable harvesting of wasted mechanical energy, leading to a signifi cant interest in data -driven research on these materials. This study presents t he design of PiezoTensorNet, a comprehensive framework that encompasses a hierar chical classification neural network for crystal point group determination and m odular ensembles of regression -based multi -dimensional models for predicting piezoelectric tensors.”
GliwicePolandEuropeCyborgsEmergi ng TechnologiesMachine LearningSilesian University of Technology
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