摘要
针对传统的基于线性回归预测建模方法只能适应简单的预测建模和只能预测未来窗口平均值的不足,提出了基于基因表达式编程(gene expression programming,GEP)的多数据流预测方法。在多数据流环境中使用滑动窗口对多数据流的划分方法,给出了多数据流环境中的数据流名称的定义,揭示了这些数据流之间存在的映射关系;进而提出了对多数据流进行预处理的方法,并建立了基于GEP的多数据流的自适应预测模型。使用真实数据进行实验,验证了算法的有效性。
A prediction algorithm for multi-data stream based on gene expression programming（GEP） was proposed for compensating the shortage that the traditional linear regression method could only adapt to a simple prediction model and predict AVG in the future window.A method of using sliding windows to partition the data stream was given in the multi-data stream.The main concept of Multi-Streams was defined,and the map relation in it was revealed.An algorithm was given to pre-treat the multi-data stream according the map relation and the sliding windows above.An adaptive forecasting model was put forward based on DSMA-GEP in the multi-data stream.Experience with real data showed that the method was efficient.
出处
《山东大学学报（理学版）》
CAS
CSCD
北大核心
2010年第7期50-54,共5页
Journal of Shandong University(Natural Science)
基金
国家自然科学基金资助项目(60763012)
广西高等学校优秀人才资助计划项目(RC2007022)
广西新世纪十百千人才工程专项基金资助项目(2006220)
关键词
预测建模
基因表达式编程
多数据流
prediction model
gene expression programming
multi-data stream
