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对铜铅锌铁尾矿、粉煤灰和氧化铝工业赤泥三种浆体的摩阻损失进行了试验研究。在试验研究结果和前人工作基础上，利用人工神经网络法对管道内浆体摩阻损失进行拟合和预测。结果表明，预测浆体摩阻损失与实测浆体摩阻损失相吻合。
The friction loss of three kinds of slurry of copper-lead-zinc-iron tailings, fly ash and alumina industrial red mud was studied. Based on the experimental results and predecessors’ work, artificial neural network method is used to fit and predict the friction loss in the pipeline. The results show that the predictions of slurry friction loss are consistent with those of the measured slurry friction loss.