DocumentCode
554846
Title
Research of neural network model prediction strategy based on PSO-BP algorithm
Author
Biying Zhou
Author_Institution
Sch. of Inf. & Technol., Northwest Univ., Xi´an, China
Volume
8
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
4077
Lastpage
4080
Abstract
In the nonlinear model prediction, it is often difficult to obtain accurate nonlinear mathematical model, and therefore prediction accuracy is affected. Through combining particle swarm algorithm with BP algorithm, this paper puts forward a PSO-BP algorithm to improve BP algorithm, and also applies it to neural network model prediction to improve the accuracy of the nonlinear model prediction.
Keywords
adaptive control; backpropagation; neural nets; nonlinear control systems; particle swarm optimisation; predictive control; BP algorithm; PSO-BP algorithm; neural network model prediction strategy; nonlinear mathematical model; nonlinear model prediction; particle swarm algorithm; Accuracy; Adaptation models; Mathematical model; Particle swarm optimization; Prediction algorithms; Predictive models; Training; BP neural networks; Nonlinear model prediction; Particle swarm algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location
Harbin, Heilongjiang
Print_ISBN
978-1-61284-087-1
Type
conf
DOI
10.1109/EMEIT.2011.6023949
Filename
6023949
Link To Document