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| 摘要: |
| 本文研究了提高灰色GM (1,1)模型预测精度的问题.利用复合函数变换对原始数据序列经过一定处理的基础上同时优化模型的背景值和初始值的方法,获得了比改进单个模型条件更高预测精度的GM (1,1)模型,推广了灰色预测模型的适用范围. |
| 关键词: 灰色理论 GM (1,1)模型 数据变换 初始条件 背景值 |
| DOI： |
| 分类号:O175.7 |
| 基金项目:国家自然科学基金资助(61263004);甘肃省科技支撑计划项目基金资助(090GKCA009;1304GKCA023);兰州市科技攻关计划项目基金资助(2013-4-18). |
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| OPTIMIZED GM (1,1) MODEL BASED ON DATA TRANSFORMATION TECHNOLOGY |
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TANG Min-an,LI Ying
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| Abstract: |
| In this paper,we study the accuracy of grey GM (1,1) forecasting model improvement.Using the composite function transformation to deal with the original data sequence,and optimizing the background value and initial value of the model,we obtain a grey forecasting model which has a higher prediction accuracy than single condition improvement GM (1,1) model.The study extends the scope of GM (1,1) forecasting model. |
| Key words: grey theory GM(1,1) model data transformation initial condition background value |
