基于穆斯堡尔参数的人工神经网络识别矿物的方法

摘要

采用改进型反向传播人工神经网络，以含铁矿物穆斯堡尔参数作为样本，通过神经网络的训练，能很好地识别矿物，从而有效地提高了对矿物的识别本领。%Minerals have been identified using Mɑssbauer parameters and artificial neural networks(ANN). The reported Mɑssbauer parameters of minerals were used to train an ANN called the improved back-propagation network. The excellent corrective ability indicates that it is probably an alternative method in M ssbauer data processing.