Clustering analysis based on adaptive genetic algorithm for performance assessment

Author

Gao Xiangpeng ; Jianhua Wang ; Shan Liang

Author_Institution

Training Dept., Shenyang Artillery Acad., Shenyang, China

fYear

2014

fDate

May 31 2014-June 2 2014

Firstpage

1682

Lastpage

1686

Abstract

This paper analyses and studies genetic algorithm and classical clustering algorithms, and then the demand analysis and design of the personnel management system of Shenyang Administration College. The adaptive crossover probability and adaptive mutation probability are proposed, which consider the influence of every generation to algorithm and the effect of different individual fitness in every generation. Theory and experiment shows that the algorithm can concluded some results of having meaning practically to guide college personnel management.

Keywords

educational administrative data processing; further education; genetic algorithms; pattern clustering; probability; Shenyang Administration College; adaptive crossover probability; adaptive genetic algorithm; adaptive mutation probability; clustering algorithm; clustering analysis; college personnel management; personnel management system; Algorithm design and analysis; Clustering algorithms; Educational institutions; Genetic algorithms; Heuristic algorithms; Sociology; Statistics; adaptive genetic algorithm; cluster analysis; performance assessment;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (2014 CCDC), The 26th Chinese

Conference_Location

Changsha

Print_ISBN

978-1-4799-3707-3

Type

conf

DOI

10.1109/CCDC.2014.6852439

Filename

6852439