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一种混合的模糊时间序列预测模型
  • ISSN号：1001-7402
  • 期刊名称：《模糊系统与数学》
  • 时间：0
  • 分类：TP274[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构：[1]大连理工大学电子信息与电气工程学部自动化系,辽宁大连116024, [2]景德镇陶瓷学院信息工程学院,江西景德镇333403
  • 相关基金：国家自然科学基金资助项目（61175041）; 高等学校博士学科点专项科研基金（博导类）资助项目（20110041110017）
作者： 董淑丽[1], 邱望仁[1,2], 刘晓东[1]
关键词： 模糊时间序列, 模糊规则, 自动聚类, 粒子群算法, Fuzzy Time Series, Fuzzy Rules, Automatic Clustering, Partical Swarm optimization
中文摘要：

随着理论与应用的需要,对模糊时间序列模型的研究和应用越来越深入。提出从论域的划分和模糊规则的提取两个方面对传统模型进行改进。模型首先采用自动聚类的方法对论域进行划分,并在此基础上建立具有权重的模糊规则;然后,利用粒子群算法对模型进行优化,进一步提高预测精度;最后,将Alabama大学入学人数作为本模型的实验数据。实验结果表明该模型是可行的,其预测结果明显优于参照预测模型。

英文摘要：

With the needs of theory and application, the research and application of fuzzy time series model has been widely studied. This paper improves the traditional fuzzy time series model from aspects of partition of interval and extraction of fuzzy rules. Firstly, the model adopts the method of automatic clustering to divide universe of discourse, and then establishs fuzzy rules with weights. Secondly, particle swarm algorithm is used to further improve the prediction accuracy. Finally, the enrollment of Alabama University is used as the experimental data for the forecasting models. The experimental results show that the proposed model outperforms the compared models.

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期刊信息
  • 《模糊系统与数学》
  • 中国科技核心期刊
  • 主管单位:国防科技大学
  • 主办单位:国防科技大学理学院 国防科技大学理学院
  • 主编：刘应明
  • 地址：湖南长沙国防科技大学理学院
  • 邮编：410073
  • 邮箱：fuzzysys@cfsm.cn
  • 电话：0731-84576220
  • 国际标准刊号：ISSN：1001-7402
  • 国内统一刊号：ISSN：43-1179/O1
  • 邮发代号:42-180
  • 获奖情况:
  • 美国《数学评论》（Mathematical Reviews）核心引...,中国科技论文统计源期刊,《中国科学引文数据库》来源期刊
  • 国内外数据库收录:
  • 美国数学评论（网络版）,德国数学文摘,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）
  • 被引量:8133