
1. 河南大学土木建筑学院
2. 河南大学地理与环境学院
3. 河南省建筑设计研究院有限公司
Published:2024
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王浩, 晏田田, 郭剑波, et al. 基于Stacking集成算法的抛石护岸水毁破坏预测研究[J]. 2024, (1): 185-188.
王浩, 晏田田, 郭剑波, et al. 基于Stacking集成算法的抛石护岸水毁破坏预测研究[J]. 2024, (1): 185-188. DOI: 10.20040/j.cnki.1000-7709.2024.20231537.
抛石护岸在顶冲等极端情况下易发生水毁破坏,给人民的生命财产带来威胁。通过水槽试验获取496组样本数据,利用互信息(MI)筛选出6个关键特征属性,并采用支持向量机(SVR)、广义回归神经网络(GRNN)和随机森林(RF)等机器学习算法构建多个预测模型。然后,将这些模型作为基学习器,结合BP神经网络(BPNN)作为元学习器,采用Stacking集成学习方法构建抛石护岸破坏程度预测模型。最后,通过决定系数(R
2
)、均方根误差(R
RMSE
)及平均绝对误差(M
MAE
)等评价指标对模型性能进行评估。结果表明,Stacking模型在抛石护岸破坏高度、长度、范围上的平均R
2
为0.98、R
RMSE
为0.02、M
MAE
为0.03
相较于单一模型(SVR、GRNN、RF)
Stacking模型的R
RMSE
、M
MAE
皆为最小,R
2
最高。在抛石护岸水毁破坏程度的预测中,融合的Stacking模型展现出更高的准确性与稳定性。
林泳恩,孟越,杜懿,王大洋,王大刚.堆叠集成模型径流预报效果的影响因素研究[J].水文,2023(01).
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grid.254148.e, 0000 0001 0033 6389, College of Civil Engineering and Architecture, China Three Gorges University, 443002, Yichang, Hubei, China,grid.254148.e, 0000 0001 0033 6389, Key Laboratory of Disaster Prevention and Mitigation of Hubei Province, China Three Gorges University, 443002, Yichang, China,grid.254148.e, 0000 0001 0033 6389, College of Civil Engineering and Architecture, China Three Gorges University, 443002, Yichang, Hubei, China,grid.254148.e, 0000 0001 0033 6389, Key Laboratory of Disaster Prevention and Mitigation of Hubei Province, China Three Gorges University, 443002, Yichang, China,grid.254148.e, 0000 0001 0033 6389, College of Civil Engineering and Architecture, China Three Gorges University, 443002, Yichang, Hubei, China,grid.254148.e, 0000 0001 0033 6389, Key Laboratory of Disaster Prevention and Mitigation of Hubei Province, China Three Gorges University, 443002, Yichang, China.Prediction model of the collapse of bank slope under the erosion effect of wind-induced wave in the Three Gorges Reservoir Area, China[J].Environmental Earth Sciences,2020.
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