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
123456789101112
ω115.2014.8014.0010.8610.008.448.227.786.916.734.694.38
ω2000000000000
ω360.8059.2056.0065.1460.0067.5665.7862.2269.0967.2770.3167.50
抗压强度/MPa3.673.642.892.431.641.591.541.481.140.840.540.43
参数序号
131415161718192021222324
ω14.387.788.448.676.366.913.503.8010.576.367.093.90
ω2015.5616.8917.7312.7313.8214.0015.200014.1815.60
ω365.6346.6750.6752.0050.9155.2752.5057.0063.4363.6456.7358.50
抗压强度/MPa0.430.432.312.211.491.670.530.672.280.901.850.74