DocumentCode :
3343084
Title :
A neural network for mining large volumes of time series data
Author :
Liang, Bojian ; Austin, James
Author_Institution :
Dept. of Comput. Sci., York Univ.
fYear :
2005
fDate :
14-17 Dec. 2005
Firstpage :
688
Lastpage :
693
Abstract :
Efficiently mining large volumes of time series data is amongst the most challenging problems that are fundamental in many fields such as industrial process monitoring, medical data analysis and business forecasting. This paper discusses a high-performance neural network for mining large time series data set and some practical issues on time series data mining. Examples of how this technology is used to search the engine data within a major UK eScience Grid project (DAME) for supporting the maintenance of Rolls-Royce aero-engine are presented
Keywords :
data mining; neural nets; time series; Rolls-Royce aero-engine; UK eScience Grid project; business forecasting; data mining; industrial process monitoring; medical data analysis; neural network; time series data; Biomedical monitoring; Computer architecture; Computer industry; Computer science; Data analysis; Data mining; Databases; Mining industry; Neural networks; Search engines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2005. ICIT 2005. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-9484-4
Type :
conf
DOI :
10.1109/ICIT.2005.1600724
Filename :
1600724
Link To Document :
بازگشت