| 区间型时间序列数据的点预测方法研究 |
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| 引用本文： | 胥少卿,罗强一,梁帅. 区间型时间序列数据的点预测方法研究[J]. 系统仿真学报, 2010, 22(3) |
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| 作者姓名： | 胥少卿 罗强一 梁帅 |
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| 作者单位： | 1. 75779部队,广州,510540
2. 中国电子设备系统工程公司研究所,北京,100141 |
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| 基金项目： | 国家自然科学基金(70625005/G0104) |
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| 摘 要： | 区间型时间序列数据大量存在,但在时序数据的预测方法中,对这种类型的数据进行点预测没有相关研究。借助支持向量机(SVM),在区间时间序列数据回归算法的基础上,通过区间数据相空间重构,建立了时间序列的支持向量区间预测SVIP方法。在实验仿真环节中,通过两个仿真实例验证了该方法的良好性能,同时与采用Elman神经网络方法的预测结果进行了分析比较,说明了SVIP方法的优点。
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| 关 键 词： | 区间 预测 支持向量机 非线性 |
Study on Interval Time Series Data Value Prediction Approach |
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| XU Shao-qing,LUO Qiang-yi,LIANG Shuai. Study on Interval Time Series Data Value Prediction Approach[J]. Journal of System Simulation, 2010, 22(3) |
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| Authors: | XU Shao-qing LUO Qiang-yi LIANG Shuai |
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| Affiliation: | XU Shao-qing1,LUO Qiang-yi2,LIANG Shuai2 (1. No.75779 Troop,PLA,Guangzhou 510540,China,2. Institute of Chinese Electronic Equipment System Engineering Corp.,Beijing 100141,China) |
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| Abstract: | Interval time series data exists widely, but no related research is focused on this type of data in time series value prediction approaches. The SVM algorithm was used, based on the interval time series regression algorithm and the interval phase space reconstruction, the Support vector Interval Prediction (SVIP) approach of time series was established. The good performance of proposed approach was verified by two simulations, and the results of SVIP were compared with that of Elman NN, and then the advanta... |
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| Keywords: | interval prediction support vector machine (SVM) nonlinear |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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