| 基于关联度的高嵌入维混沌预测方法研究 |
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| 引用本文： | 蒋传文,侯志俭,张勇传. 基于关联度的高嵌入维混沌预测方法研究[J]. 系统工程与电子技术, 2002, 24(12): 65-66 |
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| 作者姓名： | 蒋传文 侯志俭 张勇传 |
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| 作者单位： | 1. 上海交通大学电力学院,上海,200030
2. 华中科技大学水电学院,湖北,武汉,430074 |
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| 基金项目： | 国家自然科学基金资助课题 (5 0 0 790 0 6) |
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| 摘 要： | 由于现有的采用欧氏距离确定相空间最邻近点的混沌预测方法对高维混沌时间序列预测的效果不太理想 ,因而首次提出以关联度代替欧氏距离来确定相空间最邻近点的思想。通过对水文径流序列预测的验证 ,在嵌入维数逐渐增大时 ,采用所提方法比现有的方法在预测精度方面有明显的提高
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| 关 键 词： | 混沌 关联度 径流预测 高嵌入维数 |
| 文章编号： | 1001-506X(2002)12-0065-02 |
| 修稿时间： | 2001-12-19 |
One High Embedded Dimensions Chaotic Forecasting Method Base on Degree of Incidence |
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| JIANG Chuan?wen+,HOU Zhi?jian+,ZHANG Yong?chuan+. One High Embedded Dimensions Chaotic Forecasting Method Base on Degree of Incidence[J]. System Engineering and Electronics, 2002, 24(12): 65-66 |
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| Authors: | JIANG Chuan?wen+ HOU Zhi?jian+ ZHANG Yong?chuan+ |
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| Affiliation: | JIANG Chuan?wen+1,HOU Zhi?jian+1,ZHANG Yong?chuan+2 |
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| Abstract: | The chaos forecasting methods used recently, which apply Euclid distance to determine the nearest point in phase space to forecast chaos time series with high dimensions, are not so effective. In this paper, one new idea based on incidence-degree instead of Euclid distance is firstly put forward to determine the nearest point in phase space. The test result of runoff forecasting series shows that the precision of runoff forecasting is greatly improved by means of the new method when the embedded dimensions is high, compared with the method used recently.; |
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| Keywords: | Chaos Degree of incidence Runoff forecasting High embedding dimension |
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