| 基于遗传算法优化的GM(1,1)模型及效果检验 |
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| 引用本文： | 李祚泳,张明,邓新民.基于遗传算法优化的GM(1,1)模型及效果检验[J].系统工程理论与实践,2002,22(8):136-139. |
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| 作者姓名： | 李祚泳 张明 邓新民 |
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| 作者单位： | 成都信息工程学院 |
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| 基金项目： | 九·五国家重点科技攻关计划 (96-911-0 8-0 3 -0 5 ) |
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| 摘 要： | 对变化较平稳的数据和变化幅度较大的非平稳数据两种序列建立的 GM(1 ,1 )模型 ,分别用加速遗传算法 (AGA)和最小二乘法 (LSM)对模型参数求解 .结果表明 ,对变化较平稳数据序列 ,两种参数求解法建立的预测模型的拟合优度和预测精度相差无几 ;对变化幅度较大的非平稳数据序列 ,基于 AGA的 GM(1 ,1 )模型的拟合优度和预测精度远高于基于 LSM的 GM(1 ,1 )模型的拟合优度和预测精度 .
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| 关 键 词： | 遗传算法 GM(1:1)模型 最小二乘法 参数优化 |
| 文章编号： | 1000-6788(2002)08-0136-03 |
| 修稿时间： | 2001年3月16日 |
Optimal Gray GM(1,1) Model Based on Genetic Algorithm and Its Verification |
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| LI Zuo\|yong,ZHANG Min,DENG Xin\|min.Optimal Gray GM(1,1) Model Based on Genetic Algorithm and Its Verification[J].Systems Engineering —Theory & Practice,2002,22(8):136-139. |
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| Authors: | LI Zuo\|yong ZHANG Min DENG Xin\|min |
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| Institution: | Chengdu University of Information Technology |
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| Abstract: | Accelerating genetic algorithm (AGA) and least square method(LSM) were used to solving the parameters of gray GM(1,1) model for the modellings of stable data sequence and unstable deta sequence, respectively. It is shown that there is little difference of the precisions of model to solving parameters between AGA and LSM for stable data sequence, but the precision of fitting and forecasting of model to solving parameters based on AGA is much more than that of LSM for unstable data sequence. |
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| Keywords: | genetic algorithm GM(1 1) model least square method parameter optimum |
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