DocumentCode :
2731084
Title :
Research on auto-composing test paper system based on improved genetic algorithm
Author :
Dongmei, Li ; Xiantong, Huang ; Xinfeng, Yang ; Xiaoxian, Jiao
Author_Institution :
Dept. of Comput. Sci. & Technol., Nanyang Inst. of Technol., Nanyang, China
fYear :
2011
fDate :
15-17 July 2011
Firstpage :
834
Lastpage :
837
Abstract :
Comosing test paper is an important part of examination system. Based on the researches on coding policy, fitness faction, genetic operation and control parameter, an improved genetic algorithm is advanced for the auto-composing test paper system. It is an efficient way to overcome the premature convergence and the genetic drifting, and at the same time,to prevent the colony coming into the partial optimal solution considering the colony diversity by scaling the fitness faction and building the adaptive crossover probability and mutation probability. Experiment shows that the improved genetic algorithm cold compose test paper more efficiency.
Keywords :
genetic algorithms; intelligent tutoring systems; adaptive crossover probability; auto-composing test paper system; coding policy; colony diversity; control parameter; examination system; fitness faction; genetic drifting; genetic operation; improved genetic algorithm; mutation probability; premature convergence; Biological cells; Convergence; Encoding; Genetic algorithms; Genetics; Optimization; Search problems; auto-composing test paper; fitness faction; genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2011 IEEE 2nd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-9699-0
Type :
conf
DOI :
10.1109/ICSESS.2011.5982470
Filename :
5982470
Link To Document :
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