| 基于灰色支持向量机的新型预测模型 |
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| 引用本文： | 唐万梅. 基于灰色支持向量机的新型预测模型[J]. 系统工程学报, 2006, 21(4): 410-413 |
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| 作者姓名： | 唐万梅 |
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| 作者单位： | 内蒙古大学数学系,内蒙古,呼和浩特,010021;重庆师范大学数学与计算机科学学院, 重庆 400047 |
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| 基金项目： | 国家自然科学基金资助项目(1017111810471159)，教育部重点项目资助项目，教育部“新世纪优秀人才支持计划”资助项目，重庆师范大学校级科研项目(05XLY017)，重庆市教委项目(KJ060818) |
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| 摘 要： | 分析了灰色预测方法和支持向量机各自的优缺点,提出了将二者相结合的一种新的预测模型———灰色支持向量机预测模型.新模型发挥了灰色预测方法中“累加生成”的优点,弱化了原始序列中随机扰动因素的影响,增强了数据的规律性,同时避免了灰色预测方法及模型存在的理论缺陷.实验结果表明文章所提出的预测模型有效可靠,为提高预测精度提供了新的途径.
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| 关 键 词： | 灰色系统 支持向量机 时间序列 GM(1 1)模型 |
| 文章编号： | 1000-5781（2006）04-0410-04 |
| 收稿时间： | 2005-08-08 |
| 修稿时间： | 2005-08-082006-03-25 |
New forecasting model based on grey support vector machine |
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| TANG Wan-mei. New forecasting model based on grey support vector machine[J]. Journal of Systems Engineering, 2006, 21(4): 410-413 |
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| Authors: | TANG Wan-mei |
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| Affiliation: | Department of Mathematics, Inner Mongolia University, Hohhot 010021, China; Department of Mathematics and Computer Sciences, Chongqing Normal University, Chongqing 400047, China |
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| Abstract: | The advantages and disadvantages of grey forecasting methods and support vector machine(SVM) are analyzed respectively,this article proposes a new forecasting model of grey support vector machine.The new model develops the advantages of accumulation generation in the grey forecasting method,weakens the effect of stochastic-disturbing factors in original sequence,strengthens the regularity of data,and avoids the theoretical defects existing in the grey forecasting model.The simulation results show that the forecasting model is effective and reliable and offers a new way to improve the forecasting accuracy. |
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| Keywords: | grey system support vector machine time sequence GM(1 1) model |
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