融合全监督学习的半监督矿石粒度预测算法
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姜志宏,陈澳
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Semi-supervised Ore Granularity Prediction Algorithm Incorporating Fully Supervised Learning
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Zhihong JIANG,Ao CHEN
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表4 高置信度伪标签样本数据(部分数据)
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Table 4 High-confidence pseudo-label sample data(partial data)
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矿石粒级 /mm | 图像识别矿石粒度分布/% | 加权算术平均粒度/mm | 标准差 | 偏差 系数 | 模型预测矿石粒度分布/% |
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+5~10 | 0.33 | 2.566 | 1.161 | 0.170 | 0.318 | -5 | 0.357 | 0.822 | 0.396 | 0.060 | 0.377 | +10 | 0.366 | 3.468 | 1.504 | 0.221 | 0.285 | -5 | 0.296 | 0.867 | 0.383 | 0.055 | 0.393 | +10 | 0.311 | 3.167 | 1.606 | 0.254 | 0.297 | -5 | 0.389 | 0.792 | 0.401 | 0.063 | 0.279 | +10 | 0.305 | 3.156 | 1.600 | 0.254 | 0.302 | +5~10 | 0.305 | 2.367 | 1.200 | 0.190 | 0.416 | +5~10 | 0.321 | 2.515 | 1.176 | 0.175 | 0.350 | -5 | 0.332 | 0.838 | 0.392 | 0.059 | 0.318 | +10 | 0.366 | 3.468 | 1.530 | 0.221 | 0.386 | +5~10 | 0.340 | 2.601 | 1.148 | 0.166 | 0.280 | -5 | 0.360 | 0.803 | 0.388 | 0.060 | 0.324 | +10 | 0.310 | 3.363 | 1.507 | 0.224 | 0.402 | +5~10 | 0.380 | 2.522 | 1.130 | 0.168 | 0.282 | -5 | 0.310 | 0.841 | 0.377 | 0.056 | 0.305 | +10 | 0.310 | 3.313 | 1.535 | 0.232 | 0.415 | -5 | 0.250 | 0.903 | 0.367 | 0.058 | 0.325 | +5~10 | 0.380 | 2.606 | 1.114 | 0.160 | 0.396 | +5~10 | 0.390 | 2.569 | 1.114 | 0.163 | 0.325 | +10 | 0.300 | 3.150 | 1.596 | 0.253 | 0.388 | -5 | 0.390 | 0.788 | 0.399 | 0.063 | 0.282 | … | | | | | |
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