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计算机工程 ›› 2008, Vol. 34 ›› Issue (10): 176-177. doi: 10.3969/j.issn.1000-3428.2008.10.064

• 人工智能及识别技术 • 上一篇    下一篇

AGM(1,1)模型的研究及应用

陈 霞1,邱桃荣1,蔡 洪2,魏玲玲1   

  1. (1. 南昌大学信息技术工程学院,南昌 330031;2. 兄弟高科技(深圳)有限公司信息部开发系,深圳 518114)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-05-20 发布日期:2008-05-20

Research and Application of AGM(1,1) Model

CHEN Xia1, QIU Tao-rong1, CAI Hong2, WEI Ling-ling1   

  1. (1. School of Information Technology Engineering, Nanchang University, Nanchang 330031; 2. Development Faculty, Information Department of Shenzhen Xiongdi High-tech. Co. Ltd., Shenzhen 518114)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-05-20 Published:2008-05-20

摘要: 传统灰色模型GM(1, 1)是一种有偏差的指数模型,具有所需数据少、预测精度高和无需先验信息等优点,但有时预测效果不佳。基于这种情况,该文提出改进的灰色预测模型AGM (1, 1)及建模步骤,利用该模型实例预测某省参加国内游的年度总人数,并与传统的灰色预测模型结果相比较。结果表明,改进后的灰色预测模型精度更高、误差更小、简捷、实用,能够为相关部门的决策提供科学的理论 依据。

关键词: 灰色系统理论, 灰色预测, 灰色模型, 改进的灰色模型

Abstract: The conventional grey model is a kind of unbiased exponential models with the characteristics of less date, high precision and without the prior information. However, it can not get the expected results sometimes. According to the facts, an amendatory grey model (AGM (1, 1) for short) and its stages are supposed, and are used to predict the yearly total number of internal travelers in one province. Prediction results of the two above grey models are compared. It shows that the amendatory grey model is of higher precision, less prediction errors, simple process and effective practicality. AGM (1, 1) can provide scientific decision references for the concerning governments.

Key words: grey system theory, grey prediction, grey model, amendatory grey model

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