Title :
GM(1, 1) model improved by artificial fish-swarm algorithm
Author :
Yao, Ru-xian ; Li, Lin
Author_Institution :
Dept. of Inf. Eng., Huanghuai Univ., Zhumadian, China
Abstract :
Taking the advantages of fast convergence, high ability of global optimization in artificial fish-swarm optimization algorithm, this paper optimizes the background sequence, time sequence error and the combination of them in grey model GM (1, 1). Practical examples for GDP prediction are given and the simulation results indicate that the improved model gives better prediction precision and may have wider applications in electric Information and control engineering.
Keywords :
grey systems; optimisation; sequences; GM(1,1) model; artificial fish swarm algorithm; global optimization; grey model; time sequence error; Accuracy; Marine animals; Modeling; Optimization; Prediction algorithms; Predictive models; Timing; artificial fish-Swarm algorithm; background sequence; grey model; time sequence error;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5778365
