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
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;
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
DOI :
10.1109/ICISE.2010.5691441