An Online Trend Analysis Method for Measuring Data Based on Historical Data Clustering

摘要：

　　It is important to analyze and predict the measuring data trend in industrial measuring and controlling process.The paper intro duces a method for predicting the trend of the current measuring data based on clustering the historical data.It calculates the similarities of the current trend and the bases result from the clustering.And with these similarities, the future trend of the current measuring data can be predicted , the combination of the above bases representing low fre quency and a reviser representing high frequency.The simulation shows the weights of high or low frequency have effect on the precision of pre dict results.It is also found that the proposed method can predict more precisely than the RBFNNs method in high frequency.

关键词： Trend analysis predicting historical data clustering

作者: Jianfeng Qu Maoyun Guo Yi Chai Zhimin Yang Tao Zou Tian Lan Zhenglei Liu

作者单位: School of Automation at the Chongqing University, No.174 Shazhengjie, Shapingba, Chongqing, 400044, China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 137-145

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）