摘要
Robotics&Machine Learning Daily News的一位新闻记者兼工作人员新闻编辑每日新闻-机器学习的新数据在一份新的报告中呈现。据波兰Gliwice的新闻报道，NEWSRX编辑称，“压电器件为可持续地收集废弃的机械能提供了许多机会，导致人们对这些材料的数据驱动研究产生了极大的兴趣。本研究介绍了压电传感器网络的设计，一个综合的框架，包括用于确定晶点群的层次分类神经网络和用于预测压电张量的基于回归的多维模型的模块集合。
Abstract
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.”
NETL
NSTL