| 分数阶傅里叶变换联合支持向量机的建筑物变形预测 |
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| 引用本文： | 古 巍,李 倩,陈代果.分数阶傅里叶变换联合支持向量机的建筑物变形预测[J].大地测量与地球动力学,2022,42(12):1239-1245. |
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| 作者姓名： | 古 巍 李 倩 陈代果 |
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| 摘 要： | 提出一种分数阶傅里叶变换(fractional Fourier transformation, FrFT)与支持向量机(support vector machine, SVM)相结合的建筑物变形组合预测模型。首先利用FrFT对变形时间序列进行多尺度分析，将复杂时间序列分解为一系列结构较为简单的子序列；然后利用SVM对每个子序列分别建立预测模型，通过将各个子序列的预测结果进行综合叠加，得到最终预测结果；同时考虑到SVM模型参数选择的难题，提出一种改进果蝇优化算法(improved fruit fly optimization algorithm, IFOA)对其进行全局寻优，提升预测性能。以西南地区某混凝土坝变形实测数据为例开展验证实验，结果表明，本文组合预测模型能够充分挖掘数据中隐含的趋势性和规律性信息，获得较高的预测精度。
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| 关 键 词： | 分数阶傅里叶变换 支撑向量机 果蝇优化算法 组合模型 建筑物变形预测 |
Building Deformation Prediction Method Based on FrFT Combined with SVM |
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| GU Wei,LI Qian,CHEN Daiguo.Building Deformation Prediction Method Based on FrFT Combined with SVM[J].Journal of Geodesy and Geodynamics,2022,42(12):1239-1245. |
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| Authors: | GU Wei LI Qian CHEN Daiguo |
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| Abstract: | We propose a combined prediction model of building deformation based on fractional Fourier transform(FrFT) and support vector machine(SVM). First, FrFT is used for multi-scale analysis of deformation time series, and the complex time series is decomposed into a series of subsequences with relatively simple structure. Then, we use SVM to establish prediction models for each subsequence, and the final prediction results are obtained by comprehensively superimposing the prediction results of each subsequence. At the same time, considering the difficult problem of parameter selection of SVM model, we propose an improved fruit fly optimization algorithm(IFOA) to globally optimize it and improve the prediction performance. Taking the measured deformation data of a concrete dam in Southwest China as an example, the results show that the proposed combined prediction model can fully mine the trend and regularity information hidden in the data and obtain high prediction accuracy. |
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| Keywords: | fractional Fourier transform(FrFT) support vector machine(SVM) fruit fly optimization algorithm combination model building deformation prediction |
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