DocumentCode :
2839989
Title :
Modeling and simulation of the knowledge propagation of group nonlinear learning based on the complex network
Author :
Qu, Shaocheng ; Tian, Wenhui ; Li, Sha
Author_Institution :
Dept. of Inf. & Technol., Huazhong Normal Univ., Wuhan, China
fYear :
2010
fDate :
26-28 May 2010
Firstpage :
4387
Lastpage :
4390
Abstract :
A knowledge propagation model of group nonlinear learning on complex network is discussed. According to the characteristics of knowledge propagation in the general group learning network, the Cobb-Dauglas generator function is introduced to establish the knowledge propagation model of group nonlinear learning. Through considering self-motivation of excellent individual and repellency of laggard individual, an improved knowledge propagation model is proposed. Simulation results show that propagation speed and distribution of knowledge will increase with the stochastic degree of networks under the same conditions.
Keywords :
complex networks; group theory; knowledge representation; learning (artificial intelligence); stochastic processes; Cobb-Dauglas generator function; complex network; group nonlinear learning; knowledge propagation model; laggard individual; self-motivation; stochastic degree; Character generation; Cognition; Complex networks; Diseases; Electronic mail; Information science; Neuroscience; Numerical simulation; Production; Stochastic processes; Complex Network; Knowledge Propagation; Nonlinear Learning; Numerical Simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
Type :
conf
DOI :
10.1109/CCDC.2010.5498361
Filename :
5498361
Link To Document :
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