基于粒子群算法优化BP神经网络的溶浸开采浸出率预测

卜斤革,陈建宏

Based on Particle Swarm Algorithm to Optimize the BP Neural Network of Leaching Rate Prediction in Leaching Mining

Jinge BU,Jianhong CHEN

表1 训练组样本数据

Table 1 Sample data of training group

编号 温度/℃ 时间/h 固液比/（mL·g-1） 搅拌速度/（r·min-1） HCl浓度/（mol·L-1） 浸出率/% 1 85 1 10 300 4 48.17 2 85 5 8 300 4 84.73 3 85 3 10 500 3 85.06 4 85 4 10 300 3 83.75 5 85 3 10 300 4 76.75 6 85 1 10 300 3 46.25 7 85 5 10 300 1 12.03 8 85 1 10 500 3 58.32 9 85 4 10 900 3 90.93 10 85 5 10 300 3 90.50 11 85 3 10 300 2 51.19 12 85 5 6 300 4 76.00 13 85 3 10 300 1 10.75 14 85 2 10 300 4 64.25 15 85 4 12 300 4 91.08 16 85 1 10 300 2 36.75 17 85 2 10 300 1 10.24 18 85 1 12 300 4 59.07 19 85 1 6 300 4 44.14 20 85 5 10 900 3 93.75 21 85 1 10 900 3 74.21 22 85 1 10 300 4 47.25 23 85 2 10 900 3 88.00 24 85 3 12 300 4 87.78 25 85 2 8 300 4 63.65 26 85 5 10 300 4 93.06 27 85 5 12 300 4 93.58 28 85 4 10 300 4 86.25 29 85 1 10 700 3 63.53 30 85 3 6 300 4 65.57 31 85 5 6 300 4 76.00 32 85 4 10 300 1 11.01 33 85 4 10 500 3 89.96 34 85 5 10 300 4 93.06 35 85 2 10 500 3 72.67 36 85 2 10 300 4 66.20 37 85 5 10 500 3 93.24 38 85 2 10 700 3 74.61 39 85 4 10 700 3 91.48 40 85 5 10 300 2 66.25