摘要
一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-在一份新的报告中讨论了机器学习的研究结果。根据NewsRx记者在印度浦那的新闻报道，研究表明：“聚偏氟乙烯(PVDF)的压电特性是β相内p聚合物链的全反式构型的结果，主要是通过电钉扎技术实现的。本文采用集成学习方法，如AdaBoost和Random Forest，研究了对静电纺丝法制备的PVDF薄膜β相的预测。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting originating in Pune, India, by NewsRx journalists, research stated, “The piezoelectric characteristic s of polyvinylidene fluoride (PVDF) result from the all-trans configuration of p olymer chains within the beta-phase, predominantly achieved through the electros pinning technique. In this paper, the prediction of the beta-phase in PVDF films produced via electrospinning is investigated using ensemble learning methods su ch as AdaBoost and random forest.”
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