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Predictive modeling of large-scale sequential curves based on clustering

  • Chinese Academy of Sciences

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Traditional approach to predict large-scale sequential curves is to build model separately according to every curve, which causes heavy and complicated modeling workload inevitably. A new method is proposed in this paper to solve this problem. By reducing model types of curves, clustering curves and modeling by clusters, the new method simplifies modeling work to a large extent and reserves original information as possible in the meantime. This paper specifies the theory and algorithm, and applies it to predict GDP curves of multi-region, which confirms practicability and validity of the presented approach.

源语言英语
主期刊名Computational Science - ICCS 2008 - 8th International Conference, Proceedings
486-493
页数8
版本PART 2
DOI
出版状态已出版 - 2008
活动8th International Conference on Computational Science, ICCS 2008 - Krakow, 波兰
期限: 23 6月 200825 6月 2008

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编号PART 2
5102 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议8th International Conference on Computational Science, ICCS 2008
国家/地区波兰
Krakow
时期23/06/0825/06/08

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