DocumentCode :
3730415
Title :
Team performance prediction based on an evolutionary algorithm
Author :
Ni Li; Wenqing Huai; Jing Gong; Xiang Li
Author_Institution :
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
fYear :
2015
Firstpage :
574
Lastpage :
579
Abstract :
In order to better adapt to complexity of environment and uncertainty of tasks, a team with high performances has become a key to improve productivity and achieve organizational success. However, team modeling is extremely complex, involving research on individual model and interaction between individuals. Based on using agents to build individual models, this paper proposed an organization cognitive behavior model as well as putting forward an interaction model based on interactive distances to quantitatively describe mutual influence between individuals. At the same time, an improved evolutionary algorithm is applied to deduce an organization´s behavior and predict its performance. Finally, through analysis of simulation results, the proposed model is proved to be in line with actual situations.
Keywords :
"Organizations","Object oriented modeling","Standards organizations","Evolutionary computation","Market research","Analytical models","Computational modeling"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
Type :
conf
DOI :
10.1109/FSKD.2015.7382006
Filename :
7382006
Link To Document :
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