储层预测的代价敏感主动学习算法

汪敏,赵飞,闵帆

Reservoir prediction through cost⁃sensitive active learning

Min Wang,Fei Zhao,Fan Min

表4 不同缺失率下ALES算法和其他六种对比算法的平均代价比较

Table 4 The average cost of ALES and other six algorithms on different missing ratios

10% NB kNN J48 CALF GESI BPCA ALES Well_01 0.5343 0.2990 0.9412 0.3578 0.4118 0.3137 0.1485 Well_02 1.0365 1.3223 1.3688 0.9023 1.3223 0.8837 0.7601 Well_03 0.6802 0.3230 0.2940 0.2304 0.2473 0.3789 0.2438 MeanRank 5.38 4.25 5.63 3.13 4.5 3.88 1.25 30% NB kNN J48 CALF GESI BPCA ALES Well_01 0.5245 0.6618 0.7255 0.6294 0.6716 0.6176 0.2490 Well_02 1.2027 1.3156 1.0963 0.8731 1.1362 0.7973 0.7734 Well_03 0.4584 0.4550 0.3900 0.4465 0.4001 0.4738 0.3745 MeanRank 4.63 5.38 4.38 3.88 4.63 4.13 1.00 50% NB kNN J48 CALF GESI BPCA ALES Well_01 0.8775 0.8333 0.7990 0.4480 0.8137 0.5637 0.3814 Well_02 1.5349 1.4684 1.2292 0.9422 1.4219 0.8704 0.7794 Well_03 0.7669 0.7525 0.7178 0.6512 0.9347 0.7115 0.5261 MeanRank 6.13 5.38 4.13 2.88 5.38 3.13 1.00