.png){kind=icon}
返回
Adaptive and high-precision grey forecasting model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2008.12.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Although the grey forecasting model has been successfully employed in various fields and demonstrated promising results, literatures show its performance still could be improved. Therefore, a new model named EFGMm(1, 1) is proposed in this paper by eliminating the error term resulted from the traditional calculation of background value with an integration equation to substitute for such error term. In addition, Fourier series and exponential smooth technique have also been integrated into the new model to reduce the periodic and stochastic residual errors, respectively. An illustrative example of building material stock index is adopted for demonstration. Results show that the proposed model can increase the prediction accuracy, particularly when the system is instable. (C) 2008 Elsevier Ltd. All rights reserved.
Keyword:
Background value
Building material stock index
Exponential smooth technique
Fourier series
Grey forecasting model
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
机构
引用论文
Forecast of the output value of Taiwan's opto-electronics industry using the Grey forecasting model
PREAI
分享收藏Food Informatics—Review of the Current State-of-the-Art, Revised Definition, and Classification into the Research Landscape.png)
Foods
OAAI
FoodsIF0
OAAI分享收藏
查看更多内容