基于神经网络与遗传算法的多目标充填料浆配比优化

肖文丰,陈建宏,陈毅,王喜梅

Optimization of Multi-objective Filling Slurry Ratio Based on Neural Network and Genetic Algorithm

Wenfeng XIAO,Jianhong CHEN,Yi CHEN,Ximei WANG

表1 充填料浆配比学习样本数据

Table 1 Filling slurry ratio data of learning samples

参数 序号 1 2 3 4 5 6 7 8 9 10 11 12 ω1 15.20 14.80 14.00 10.86 10.00 8.44 8.22 7.78 6.91 6.73 4.69 4.38 ω2 0 0 0 0 0 0 0 0 0 0 0 0 ω3 60.80 59.20 56.00 65.14 60.00 67.56 65.78 62.22 69.09 67.27 70.31 67.50 抗压强度/MPa 3.67 3.64 2.89 2.43 1.64 1.59 1.54 1.48 1.14 0.84 0.54 0.43 参数 序号 13 14 15 16 17 18 19 20 21 22 23 24 ω1 4.38 7.78 8.44 8.67 6.36 6.91 3.50 3.80 10.57 6.36 7.09 3.90 ω2 0 15.56 16.89 17.73 12.73 13.82 14.00 15.20 0 0 14.18 15.60 ω3 65.63 46.67 50.67 52.00 50.91 55.27 52.50 57.00 63.43 63.64 56.73 58.50 抗压强度/MPa 0.43 0.43 2.31 2.21 1.49 1.67 0.53 0.67 2.28 0.90 1.85 0.74