DocumentCode :
528592
Title :
A Revised Approach to Detect Time Series Correlation
Author :
Wang, Lei ; Li, Shushan
Author_Institution :
Coll. of Inf. Sci. & Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
Volume :
1
fYear :
2010
fDate :
26-28 Aug. 2010
Firstpage :
321
Lastpage :
324
Abstract :
This paper proposes the concept of function correlation, which takes the concept of linear correlation and concept of non-linear correlation together with a unified. On this basis, a BP neural network model was constructed to approximate the correlation function. Experimental results show that the correlation function determined by BP neural network can be a higher correlation coefficient.
Keywords :
backpropagation; neural nets; time series; BP neural network model; correlation coefficient; linear correlation function; nonlinear correlation function; time series correlation detection; Approximation methods; Artificial neural networks; Correlation; Indexes; Neurons; Time series analysis; Transfer functions; correlation coefficient; neural network; time series analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2010 2nd International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4244-7869-9
Type :
conf
DOI :
10.1109/IHMSC.2010.86
Filename :
5590898
Link To Document :
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