首页|基于KPCA-NGO-LSSVM的混凝土坝变形预测模型

基于KPCA-NGO-LSSVM的混凝土坝变形预测模型

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变形作为最直观的监测指标,常用来反映大坝的服役性态变化.为建立更加符合混凝土坝变形的预测模型,实现更高精度的混凝土坝变形预测,针对混凝土坝变形序列呈现不确定性和非线性的特征,将核主成分分析(KPCA)引入最小二乘支持向量机(LSSVM)来约简因子关系,降低预测模型的输入维数和复杂度,同时使用北方苍鹰优化算法(NGO)对最小二乘支持向量机进行参数寻优,构建了基于KPCA-NGO-LSSVM的混凝土坝变形预测模型.工程实例表明,KPCA-NGO-LSSVM模型相比传统多元线性回归(MLR)、LSSVM、KPCA-LSSVM的预测值与实际值的拟合效果更好,预测精度更高,能更有效地预测混凝土坝变形.
Deformation Prediction Method of Concrete Dam Based on KPCA-NGO-LSSVM
As the most intuitive monitoring index,deformation is often used to reflect the change of the service be-havior of the dam.In order to establish a prediction model which is more in line with the deformation of concrete dam and realize more accurate prediction of dam deformation,aiming at the uncertain and nonlinear characteristics of deformation sequence of concrete dam,kernel principal component analysis(KPCA)is introduced into least square support vector ma-chine(LSSVM)to reduce the factor relationship and reduce the input dimension and complexity of the prediction model.At the same time,the northern goshawk optimization algorithm(NGO)is used to optimize the parameters of the least square support vector machine,and the concrete dam deformation prediction model based on KPCA-NGO-LSSVM is con-structed.The engineering example shows that the fitting effect between the predicted value and the actual value of KPCA-NGO-LSSVM model is better than that of traditional multiple linear regression(MLR),LSSVM and KPCA-LSSVM,and the prediction accuracy is higher,which can be used to predict the deformation of concrete dam more effectively.

concrete damkernel principal component analysisnorthern goshawk optimization algorithmleast square support vector machinedeformation prediction

詹明强、陈波、袁志颖

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福建水口发电集团有限公司,福建 福州 350001

河海大学水利水电学院,江苏 南京 210098

中国电建集团中南勘测设计研究院有限公司,湖南 长沙 410014

混凝土坝 核主成分分析 北方苍鹰算法 最小二乘支持向量机 变形预测

国家自然科学基金项目国家自然科学基金项目国家重点实验室基本科研业务费项目

5207904952239009522012272

2024

10.20040/j.cnki.1000-7709.2024.20231586

水电能源科学
中国水力发电工程学会 华中科技大学 武汉国测三联水电设备有限公司

水电能源科学

CSTPCD北大核心
影响因子：0.525
ISSN：1000-7709
年,卷(期)：2024.42(8)
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