基于BP神经网络的磷酸铝合成数据补值模型研究

摘要

Database of AlPO syntheses contains missing values about 29% of total.In this paper,to deal with the problem of missing values,back-propagation neural networks imputes is employed on database for the first time.A large number of experimental results show that the BPimpute is competent for microporous aluminophosphates.%磷酸铝合成反应数据库中有29%的数据存在不同情况的缺失。为了处理缺失值问题，本文首次提出利用BP神经网络对其进行估计补值。在不同缺失率下，通过大量的随机实验结果证明了补值算法具有一定的有效性和可行性。