Strategy for Test Paper Composition Based on Genetic Algorithm

Hong Tao Tang

doi:10.4028/www.scientific.net/AMM.513-517.1688

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Analysis on the Adaptive Selection Process of MAS-Based Data Mining Model
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Strategy for Test Paper Composition Based on Genetic Algorithm
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Strategy for Test Paper Composition Based on...

Strategy for Test Paper Composition Based on Genetic Algorithm

Abstract:

Recently, with rapid development of computer/network technology and algorithms for composing test paper, cyber-based online examination system is a practically valuable hot research concern. In the paper, the mathematical model is created for solving problems with the online test paper composition system. Through comparative analysis of merits and shortcomings of various coding schemes, and to overcome the shortcoming that traditional genetic algorithms easily fall into premature convergence, it utilizes the adaptive adjustment method of dynamic parameters and elitist strategy to improve to develop the online test paper forming scheme based on adaptive genetic algorithm. For the selection of each parameter, simulation test is conducted to obtain the solution approximate to the best one.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

1688-1691

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.1688

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Online since:

February 2014

Authors:

Hong Tao Tang*

Keywords:

Adaptive, Composing Test Paper Algorithm, Genetic Algorithm (GA), Online Examination System

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