| 一种改进的GMDH算法 |
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| 引用本文： | 张秋菊,朱帮助.一种改进的GMDH算法[J].郑州大学学报(理学版),2010,42(1). |
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| 作者姓名： | 张秋菊 朱帮助 |
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| 作者单位： | 五邑大学,系统科学与技术研究所,广东,江门,529020 |
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| 基金项目： | 国家自然科学基金资助项目,编号70471074; 广东省自然科学基金资助项目,编号9452902001004060 |
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| 摘 要： | 传统GMDH算法在进行多变量非线性建模时耗时较长,一定程度上限制了它的应用范围.针对这个问题,提出了一种改进的GMDH算法,扩大了每一个初始输入元素的信息含量,采用随机分组建立中间模型的方式代替原算法枚举出所有两两组合中间模型的方式,减少了中间模型的数量,提高了建模效率.将改进算法应用于中国GDP的趋势预测,结果表明与传统GMDH算法相比,在不牺牲预测精度的情况下,改进算法效率更高.
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| 关 键 词： | GMDH 传递函数 复杂系统 预测建模 |
An Improved GMDH Algorithm |
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| ZHANG Qiu-ju
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ZHU Bang-zhu.An Improved GMDH Algorithm[J].Journal of Zhengzhou University:Natural Science Edition,2010,42(1). |
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| Authors: | ZHANG Qiu-ju ZHU Bang-zhu |
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| Institution: | ZHANG Qiu-ju,ZHU Bang-zhu(Institute of Systems Science , Technology,Wuyi University,Jiangmen 529020,China) |
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| Abstract: | GMDH algorithm takes much time to obtain the final solutions when building nonlinear models with many variables,so its application is limited.Aimed at this problem,some improvements are implemented on the transfer functions of classical GMDH algorithm.More information is added to every initial input,and a stochastic way instead of the emumerating way is used to create the next middle layer models in order to decrease the number of middle layer models and enhance the modeling efficiency.Finally,through build... |
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| Keywords: | GMDH transfer function complex system prediction modeling |
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