Title :
The Data Mining Technique of Time-series Trending Structure Series
Author :
Gao, Xiangjun ; Du, Qiliang ; Tian, Lianfang ; Mao, Zongyuan ; Wang, Yong
Author_Institution :
Coll. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou
Abstract :
According to the inner characters of the time series, the conception of time-series trending structure series and the latest time sub-series was defined, and the time-series trending structure mining technique was presented. The technique first converted the time series waiting for mining into its trending structure series, then used the information underlying in the latest trending structure sub-series of the latest time sub-series as a guide to excavate the original time series. The model of RBF neural network was also presented to predict the trend of time series with real world data set. Experimental results reveal that the time-series trending structure mining technique is significant
Keywords :
data mining; radial basis function networks; time series; RBF neural network; data mining; time subseries; time-series trending structure mining; trending structure series; Automation; Data mining; Educational institutions; Electronic mail; Information science; Intelligent control; Neural networks; Predictive models; RBF Neural Network; latest trending structure sub-series; time series; trending structure series;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714235
