DocumentCode
2152817
Title
The application of improved Empirical Mode Decomposition Algorithm algorithm to the intelligent mechanical ventilation bed
Author
Li, Hua-lai ; Liu, Zai-wen ; Xu, Ji-ping ; Xiao-yi, Wang ; Xu, Yuan-da
Author_Institution
Department of computer and information engineering, Beijing Technology and business university, China
fYear
2010
fDate
4-6 Dec. 2010
Firstpage
4759
Lastpage
4762
Abstract
To forecast precisely the time series to the intelligent mechanical ventilation bed online, the improved Empirical Mode Decomposition Algorithm was introduced novel EMD algorithm (NEMD) was gotten in this paper by using piecewise power function to generate envelope curves and extending their end points. The improved EMD was utilized to decompose the de-noised data, Next, the BP Neural Network (NN) and Least Square Support Vector Machines (LSSVM) were used to predict the low frequency items and high frequency items of the decomposed sequence data. The modeling and simulation results indicate that the algorithm that the improved EMD algorithm was introduced in realized online can forecast the time series precisely.
Keywords
Artificial neural networks; Computational modeling; Computer simulation; Computers; Prediction algorithms; Time series analysis; Ventilation; Empirical Mode Decomposition; Interpolation algorithm; Power function; neural network; time series;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location
Hangzhou, China
Print_ISBN
978-1-4244-7616-9
Type
conf
DOI
10.1109/ICISE.2010.5691441
Filename
5691441
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