Title :
Combination of intelligent prediction model based on BP neural network and its application
Author :
Ge Lei ; Dai Feng ; Wang Chunxin ; Zhai Dongkai
Author_Institution :
Dept. of Manage. Sci., Inf. Eng. Coll., Zheng-Zhou, China
Abstract :
Based on the existing theory of intelligent prediction, this paper applies BP neural network to integrate a variety of intelligent forecasting models, which makes the model approximate the trend of things well, and use back-propagation algorithm to train the network. Lastly, the author applies the integrate model to forecast the quantity of science and technology staffs. The conclusion shows that: the integrate model composed of intelligent prediction methods based on BP neural network can greatly improve the predictive accuracy, better than a single model and linear combination.
Keywords :
backpropagation; forecasting theory; neural nets; BP neural network; backpropagation algorithm; forecasting models; intelligent prediction model; linear combination; science and technology staffs; Analytical models; Genetic algorithms; Intelligent networks; Intelligent transportation systems; Neural networks; Power electronics; Power system modeling; Predictive models; Rail transportation; Technology forecasting; BP neural network; Combination; application; intelligent prediction;
Conference_Titel :
Power Electronics and Intelligent Transportation System (PEITS), 2009 2nd International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-4544-8
DOI :
10.1109/PEITS.2009.5407017