基于深度学习的滑坡灾害易发性分析
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王毅, 方志策, 牛瑞卿, 彭令
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Landslide Susceptibility Analysis based on Deep Learning
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WANG Yi, FANG Zhice, NIU Ruiqing, PENG Ling
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表6 集成模型和CNN分类器的精度评价
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Tab. 6 Performance of the proposed ensemble models and CNN classifiers
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| 模型 | ACC/% | RMSE | MAE | 敏感度 | 特异度 | | 集成模型 | Stacking | 85.09 | 0.3862 | 0.1491 | 0.8684 | 0.8333 | | Blending | 83.88 | 0.4082 | 0.1667 | 0.8070 | 0.8596 | | WA | 83.30 | 0.4082 | 0.1667 | 0.7632 | 0.9035 | | 基分类器 | 1D-CNN | 76.31 | 0.4867 | 0.2368 | 0.7105 | 0.8158 | | 2D-CNN | 78.95 | 0.4588 | 0.2105 | 0.7193 | 0.8596 | | 3D-CNN | 76.32 | 0.4866 | 0.2368 | 0.6754 | 0.8509 |
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