| 基亏遗传算法的GM（1，1，λ）改进模型 |
| |
| 引用本文： | 王国华,辛江涛,辛敏洁,张欣豫. 基亏遗传算法的GM（1，1，λ）改进模型[J]. 国外电子元器件, 2014, 0(10): 38-41 |
| |
| 作者姓名： | 王国华 辛江涛 辛敏洁 张欣豫 |
| |
| 作者单位： | [1]第二炮兵工程大学一系．陕西西安710025 [2]燕山大学电气工程学院,河北秦皇岛066004 |
| |
| 摘 要： | 研究表明，灰色GM（1，1）-N测模型中的背景值及建模序列光滑度对于模型的预测精度均有影响。针对这一问题，引入背景值构造参数入和三点平滑法，提出了基于三点平滑的GM（1，1，λ）改进模型，并利用遗传算法对引入的参数入进行了最优值搜索。最后通过实例和仿真证明改进模型优于现有的灰色模型，具有更高的模拟和预测精度。
|
| 关 键 词： | 灰色GM（1, 1）预测模型 遗传算法 三点平滑法 最优值搜索 |
Improved Grey Model based on genetic algorithm |
| |
| WANG Guo-hua,XIN Jiang-tao,XIN Min-jie,ZHANG Xin-yu. Improved Grey Model based on genetic algorithm[J]. International Electronic Elements, 2014, 0(10): 38-41 |
| |
| Authors: | WANG Guo-hua XIN Jiang-tao XIN Min-jie ZHANG Xin-yu |
| |
| Affiliation: | 1. lstDep., Second Artillery Engineering University, Xi＇an 710025, China, 2. Institute of Electric Engineering, Yanshan University, Qinhuangdao 066004, China) |
| |
| Abstract: | Researched by this paper indicates that the background value and the smoothness of modeling sequence have an effect on the prediction accuracy of the grey GM （1,1） prediction model. Aiming at this problem, the background value structure parameters λ and three-points smoothing method is introduced, what＇s more, improved grey model GM （1,1,λ） based on three- point smoothing method is proposed in this article, then, the genetic algorithm is applied to search the optimal value of λ. Finally, the improved model which has higher simulation and prediction accuracy is proved that improved model is superior to the existing grey model by an example and simulation. |
| |
| Keywords: | the grey GM （1,1） prediction model genetic algorithm three-point smoothing method search the optimal value |
| 本文献已被 维普 等数据库收录！ |
|
