BP神经网络算法在陆域天然气水合物成藏预测中的应用
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付康伟, 张学强, 彭炎
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The application of BP neural network algorithm to the prediction of terrestrial gas hydrate accumulation
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Kang-Wei FU, Xue-Qiang ZHANG, Yan PENG
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表2 算法样本
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Table 2 Sample table
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钻井 编号 | 输入 | 输出 | AMT高 阻异常 | 断裂 | 冻土 厚度 | He | Ne | SC2 | SC2H6 | SCH4 | WC2 | WC2H6 | WCH4 | DK1,2,3,7 | 1 | 1 | 0.39 | 0.25 | 0.68 | 0.06 | 0.08 | 0.10 | 0.25 | 0.18 | 0.05 | 1 | DK13-11 | 1 | 1 | 0.35 | 0.21 | 0.97 | 0.05 | 0.06 | 0.08 | 0.54 | 0.65 | 0.69 | 1 | DK12-13 | 1 | 0 | 0.30 | 0.26 | 0.72 | 0.08 | 0.10 | 0.12 | 0.28 | 0.20 | 0.06 | 1 | DK9 | 1 | 1 | 0.58 | 0.33 | 0.55 | 0.02 | 0.01 | 0.03 | 0.29 | 0.23 | 0.04 | 1 | DK11-14 | 1 | 0 | 0.61 | 0.22 | 0.49 | 0.03 | 0.03 | 0.05 | 0.23 | 0.15 | 0.01 | 1 | DK10-17 | 1 | 0 | 0.34 | 0.30 | 0.42 | 0.03 | 0.03 | 0.13 | 0.40 | 0.21 | 0.00 | 1 | DK8-19 | 0 | 1 | 0.22 | 0.21 | 0.50 | 0.01 | 0.01 | 0.02 | 0.25 | 0.16 | 0.00 | 1 | DK10 | 0 | 0 | 0.56 | 0.29 | 0.66 | 0.13 | 0.17 | 0.26 | 0.63 | 0.53 | 0.16 | 0 | DK4 | 0 | 0 | 0.51 | 0.24 | 0.63 | 0.03 | 0.04 | 0.05 | 0.53 | 0.58 | 0.26 | 0 | DK10-16 | 0 | 1 | 0.32 | 0.38 | 0.61 | 0.22 | 0.28 | 0.29 | 0.71 | 0.36 | 0.01 | 0 | DK10-18 | 0 | 1 | 0.34 | 0.09 | 0.62 | 0.02 | 0.01 | 0.02 | 0.45 | 0.42 | 0.34 | 0 | DK6 | 0 | 1 | 0.01 | 0.31 | 0.51 | 0.01 | 0.01 | 0.02 | 0.36 | 0.30 | 0.12 | 0 | DK7-20 | 0 | 0 | 0.18 | 0.34 | 0.49 | 0.01 | 0.01 | 0.02 | 0.51 | 0.27 | 0.00 | 0 | DK5-22 | 0 | 0 | 0.00 | 0.28 | 0.64 | 0.03 | 0.02 | 0.03 | 0.27 | 0.22 | 0.04 | 0 | SK0 | 1 | 1 | 0.43 | 0.26 | 0.62 | 0.05 | 0.07 | 0.08 | 0.28 | 0.25 | 0.08 | 0 | SK1 | 0 | 1 | 0.32 | 0.22 | 0.86 | 0.05 | 0.06 | 0.08 | 0.43 | 0.47 | 0.44 | 0 | SK2 | 1 | 1 | 0.51 | 0.38 | 0.59 | 0.02 | 0.01 | 0.03 | 0.34 | 0.28 | 0.06 | 0 | DK5 | 0 | 0 | 0.30 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | DK11 | 0 | 1 | 0.24 | 0.12 | 0.79 | 0.01 | 0.01 | 0.03 | 0.50 | 0.29 | 0.07 | 0 |
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