Adaboost集成学习优化的巷道围岩松动圈预测研究
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方博扬,赵国彦,马举,陈立强,简筝
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Prediction Study on Loosening Ring of Surrounding Rock Around Roadways Using the Optimized Ensemble Learning Algorithms Based on Adaboost
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Boyang FANG,Guoyan ZHAO,Ju MA,Liqiang CHEN,Zheng JIAN
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表1 样本数据
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Table 1 Database of samples
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样本编号 | 巷道埋深/m | 巷道跨度/m | 掘进断面面积/m2 | 单轴抗压强度/MPa | 节理发育程度 | 厚度/m | 样本编号 | 巷道埋深/m | 巷道跨度/m | 掘进断面面积/m2 | 单轴抗压强度/MPa | 节理发育程度 | 厚度/m |
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1 | 362 | 2.6 | 6.8 | 62.4 | 2 | 0.6 | 34 | 689 | 3.0 | 7.6 | 15.1 | 4 | 1.8 | 2 | 660 | 4.4 | 14.6 | 12.5 | 5 | 2.2 | 35 | 450 | 3.0 | 7.6 | 11.2 | 3 | 1.2 | 3 | 384 | 3.5 | 11.5 | 8.5 | 3 | 1.2 | 36 | 410 | 3.6 | 11.7 | 13.3 | 4 | 1.4 | 4 | 150 | 3.6 | 11.7 | 14.6 | 2 | 0.6 | 37 | 348 | 3.2 | 9.2 | 7.5 | 3 | 1.2 | 5 | 178 | 2.6 | 6.4 | 23.8 | 3 | 1.2 | 38 | 357 | 3.2 | 8.5 | 10.5 | 3 | 1.1 | 6 | 510 | 3.2 | 7.3 | 12.6 | 4 | 1.6 | 39 | 273 | 2.6 | 6.6 | 15.9 | 2 | 0.8 | 7 | 420 | 3.6 | 10.3 | 14.3 | 3 | 1.2 | 40 | 280 | 2.8 | 7.1 | 12.7 | 2 | 0.8 | 8 | 450 | 3.4 | 4.8 | 9.1 | 5 | 2.0 | 41 | 321 | 2.6 | 6.6 | 15.9 | 2 | 0.8 | 9 | 236 | 3.0 | 7.5 | 14.3 | 3 | 1.2 | 42 | 665 | 4.4 | 14.6 | 10.9 | 4 | 1.7 | 10 | 470 | 4.0 | 12.6 | 10.1 | 5 | 2.2 | 43 | 350 | 3.2 | 8.5 | 10.5 | 3 | 1.2 | 11 | 467 | 3.4 | 8.2 | 11.2 | 3 | 1.0 | 44 | 321 | 2.6 | 6.6 | 9.2 | 3 | 1.2 | 12 | 490 | 3.7 | 8.9 | 12.5 | 4 | 1.8 | 45 | 340 | 3.0 | 7.6 | 73.6 | 2 | 0.8 | 13 | 450 | 3.6 | 10.8 | 13.3 | 4 | 1.6 | 46 | 470 | 3.6 | 11.2 | 9.1 | 5 | 2.1 | 14 | 224 | 3.4 | 8.2 | 11.2 | 3 | 1.0 | 47 | 231 | 3.0 | 7.5 | 18.3 | 2 | 0.7 | 15 | 460 | 3.2 | 9.7 | 101.6 | 1 | 0.4 | 48 | 125 | 3.4 | 9.8 | 13.3 | 3 | 1.0 | 16 | 373 | 2.5 | 6.3 | 14.6 | 2 | 0.9 | 49 | 296 | 3.4 | 7.8 | 22.4 | 4 | 1.4 | 17 | 310 | 2.8 | 7.1 | 13.8 | 3 | 1.2 | 50 | 436 | 2.8 | 7.2 | 15.2 | 3 | 1.2 | 18 | 125 | 2.8 | 7.1 | 13.3 | 2 | 0.7 | 51 | 343 | 3.2 | 9.6 | 32.2 | 2 | 0.7 | 19 | 392 | 2.8 | 6.9 | 14.5 | 2 | 0.8 | 52 | 525 | 3.2 | 7.3 | 15.8 | 4 | 1.6 | 20 | 249 | 3.4 | 8.2 | 16.8 | 3 | 1.0 | 53 | 264 | 3.2 | 9.2 | 11.2 | 3 | 1.1 | 21 | 140 | 3.6 | 10.3 | 13.4 | 2 | 0.5 | 54 | 292 | 3.4 | 7.8 | 12.5 | 4 | 1.4 | 22 | 345 | 3.0 | 7.6 | 65.0 | 2 | 0.7 | 55 | 362 | 2.6 | 6.8 | 58.0 | 2 | 0.8 | 23 | 315 | 2.8 | 7.1 | 11.2 | 3 | 1.1 | 56 | 180 | 2.8 | 7.1 | 110.2 | 1 | 0.3 | 24 | 550 | 3.4 | 9.4 | 12.5 | 5 | 2.1 | 57 | 362 | 2.6 | 6.8 | 62.4 | 2 | 0.6 | 25 | 410 | 3.2 | 7.2 | 13.3 | 3 | 1.1 | 58 | 340 | 3.2 | 9.6 | 32.2 | 2 | 0.7 | 26 | 420 | 3.2 | 9.2 | 9.1 | 4 | 1.7 | 59 | 467 | 3.4 | 9.6 | 10.1 | 4 | 1.8 | 27 | 340 | 3.2 | 9.2 | 19.8 | 3 | 1.3 | 60 | 268 | 3.0 | 7.5 | 12.0 | 3 | 1.4 | 28 | 340 | 3.2 | 9.6 | 32.2 | 2 | 0.7 | 61 | 236 | 3.0 | 7.5 | 14.3 | 3 | 1.2 | 29 | 420 | 3.7 | 8.9 | 9.1 | 4 | 1.4 | 62 | 321 | 2.6 | 6.6 | 13.3 | 3 | 1.1 | 30 | 370 | 3.5 | 8.3 | 10.5 | 3 | 1.0 | 63 | 97 | 3.2 | 8.8 | 11.2 | 4 | 1.2 | 31 | 428 | 3.6 | 11.7 | 16.5 | 3 | 1.2 | 64 | 322 | 3.4 | 7.7 | 14.3 | 4 | 1.5 | 32 | 465 | 4.0 | 12.6 | 9.5 | 4 | 1.6 | 65 | 293 | 3.5 | 8.3 | 11.9 | 3 | 1.1 | 33 | 403 | 2.9 | 7.2 | 12.6 | 3 | 1.3 | 66 | 450 | 3.4 | 7.8 | 9.1 | 5 | 2.0 |
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