模型集群分析策略联合ELM的土壤重金属Pb含量预测
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肖烨辉, 宋妮迪, 孟盼盼, 王培俊, 范胜龙
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Prediction of lead content in soil based on model population analysis coupled with ELM algorithm
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XIAO Yehui, SONG Nidi, MENG Panpan, WANG Peijun, FAN Shenglong
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表3 3种回归模型联合各波段选择算法预测结果
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Tab.3 Prediction results of three regression models based on different wavelength selection methods
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模型 | 波长选择方法 | 变量数量 | 建模集 | 验证集 | R2 | RMSE | R2 | RMSE | RPD | RPIQ | | 全波段 | 2 001 | 0.702 | 8.450 | 0.736 | 5.426 | 1.976 | 2.560 | | CARS | 119 | 0.726 | 6.958 | 0.759 | 5.235 | 2.048 | 2.653 | PLSR | VISSA | 78 | 0.720 | 7.033 | 0.780 | 5.003 | 2.143 | 2.777 | | IVSO | 98 | 0.718 | 7.050 | 0.802 | 4.748 | 2.258 | 2.926 | | ICO | 276 | 0.720 | 7.023 | 0.813 | 4.610 | 2.325 | 3.013 | SVM | CARS | 119 | 0.643 | 7.939 | 0.735 | 5.485 | 1.954 | 2.532 | VISSA | 78 | 0.645 | 7.915 | 0.745 | 5.385 | 1.991 | 2.579 | IVSO | 98 | 0.630 | 8.075 | 0.757 | 5.252 | 2.041 | 2.645 | ICO | 276 | 0.631 | 8.069 | 0.770 | 5.116 | 2.095 | 2.715 | ELM | CARS | 119 | 0.814 | 6.338 | 0.806 | 4.703 | 2.279 | 2.953 | VISSA | 78 | 0.861 | 4.948 | 0.837 | 4.304 | 2.491 | 3.227 | IVSO | 98 | 0.899 | 4.229 | 0.858 | 4.013 | 2.671 | 3.461 | ICO | 276 | 0.877 | 4.653 | 0.863 | 3.953 | 2.712 | 3.514 |
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