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基于主成分分析与支持向量机的渠道闸前冰输移与堆积判别模型

梁乃生 脱友才 邓云 贾云霄

梁乃生, 脱友才, 邓云, 贾云霄. 基于主成分分析与支持向量机的渠道闸前冰输移与堆积判别模型[J]. 力学学报, 2021, 53(3): 703-713. doi: 10.6052/0459-1879-20-391
引用本文: 梁乃生, 脱友才, 邓云, 贾云霄. 基于主成分分析与支持向量机的渠道闸前冰输移与堆积判别模型[J]. 力学学报, 2021, 53(3): 703-713. doi: 10.6052/0459-1879-20-391
Liang Naisheng, Tuo Youcai, Deng Yun, Jia Yunxiao. CLASSIFICATION MODEL OF ICE TRANSPORT AND ACCUMULATION IN FRONT OF CHANNEL FLAT SLUICE BASED ON PCA-SVM[J]. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(3): 703-713. doi: 10.6052/0459-1879-20-391
Citation: Liang Naisheng, Tuo Youcai, Deng Yun, Jia Yunxiao. CLASSIFICATION MODEL OF ICE TRANSPORT AND ACCUMULATION IN FRONT OF CHANNEL FLAT SLUICE BASED ON PCA-SVM[J]. Chinese Journal of Theoretical and Applied Mechanics, 2021, 53(3): 703-713. doi: 10.6052/0459-1879-20-391

基于主成分分析与支持向量机的渠道闸前冰输移与堆积判别模型

doi: 10.6052/0459-1879-20-391
基金项目: 1) 四川大学水力学与山区河流开发保护国家重点实验室开放课题基金(SKHL1604)
详细信息
    作者简介:

    2) 脱友才,副研究员,主要研究方向: 寒区水力学. E-mail: tuoyoucai@scu.edu.cn

    通讯作者:

    脱友才

  • 中图分类号: TV875

CLASSIFICATION MODEL OF ICE TRANSPORT AND ACCUMULATION IN FRONT OF CHANNEL FLAT SLUICE BASED ON PCA-SVM

  • 摘要: 冬季渠道输水过程中浮冰容易在闸前形成堆积体,导致过水断面束窄,严重时影响渠道的输水效率和安全运行. 为判断渠道闸前浮冰的输移状态,开展了明渠水槽平板闸孔自由出流条件下的室内物理模型试验,提出了一种基于主成分分析与支持向量机(principal component analysis and support vectormachine,PCA-SVM)的闸前冰堆积与输移判别模型.通过相关性分析法确定输入特征间存在信息重叠,进而采用主成分分析法对特征向量进行降维,提取贡献率为86%的第一主成分和贡献率为7%的第二主成分作为输入特征,利用网格搜索方法确定多项式、高斯径向基和Sigmoid核函数的最优参数,通过混淆矩阵确定最优核函数为高斯径向基,最优核函数参数C为137,$\gamma$为0.37,建立PCA-SVM模型对试验数据进行监督学习.结果显示,模型在验证集上预测精确率为0.94,准确率为0.97,F1-Score为0.97,上游水流弗汝徳数($Fr_{1}$)和闸前水流弗汝徳数($Fr_{2}$)是渠道闸前冰输移与堆积的主要影响因素,闸孔相对开度($H/e$)和闸门相对淹没水深($H_{1}/H$)是次要影响因素.进一步将已建立的模型应用在倒虹吸口浮冰状态判别试验中,验证开发模型的分类性能.研究成果可为冬季输水渠道的调度管理和安全运行提供重要参考.

     

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  • 收稿日期:  2020-11-20
  • 刊出日期:  2021-03-10

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