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本文提出矿物分类和识别的人工神经网络模型，并选取一组标样──我国沉积碳酸盐型锰矿中菱锰矿作为研究对象，识别效率达100％。结果表明，该模型性能良好，可望成为矿物识别的有效手段。
In this paper, an artificial neural network model for classification and identification of minerals is proposed. A set of standard samples, namely, rhodochrosite in carbonate-type manganese deposits in China, are selected as the research object, and the identification efficiency is up to 100%. The results show that the model has good performance and is expected to be an effective method for mineral identification.