摘要
利用缓冲算子提高数据序列光滑性是提高灰色GM(1,1)模型预测精度的重要途径之一。在对缓冲算子和已有强化缓冲算子研究的基础上,构造了一类新的强化缓冲算子(strengthening buffer operator,SBO),有效地解决了冲击扰动数据序列在建模预测过程中常常出现的定量预测结果与定性分析结论不符的问题,实例分析结果表明:这类新的强化缓冲算子能显著提高数据预测模型的预测精度。
Enhancing the smooth of data series by using buffer operators is one of the important ways for improving the forecast precision of GM （1,1） model. Based on the present theories of buffer operators and some already existed strengthening buffer operators, some new strengthening buffer operators （SBO） are established. The problem that there are some contradictions between quantitative analysis and qualitative analysis in pretreatment for vibration data sequences is resolved effectively. An example shows the kind of new strengthening buffer operators increase the forecast precision of data forecast modal remarkably.
出处
《管理工程学报》
CSSCI
北大核心
2009年第4期153-156,共4页
Journal of Industrial Engineering and Engineering Management
基金
国家自然科学基金资助项目(70473037)
江苏省普通高校研究生科研创新计划资助项目(CX08B-039R)
江苏省青蓝工程优秀青年骨干教师资助项目(JSQL08)
关键词
SBO
算术平均强化算子
几何平均强化算子
GM(1
1)
预测精度
strengthening buffer operator
arithmetic average strengthening operator
geometry average strengthening operator
grey model （1,1）
forecast precision
