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2009•Unpublished venueRequires access

Research on Intelligent Fixing Test Paper Algorithm Based on Cultural Algorithms and Genetic Algorithm

Jiang Yong-ping, Jiang Jiao-li, Du Yuhui, Liao Yi-ming

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Abstract

According to the feature that genetic algorithm (GA) is adapted to requirement of culture algorithms (CA) framework, GA is as the population space of CA and these two Algorithms are applied to the intelligent fixing test paper strategy research by combining. This method guides the population evolution efficiently through belief space and speeds up convergence. The experimental results prove that the algorithm keeps good average fitness and high operating efficiency.

About this research paper

What this paper is about

According to the feature that genetic algorithm (GA) is adapted to requirement of culture algorithms (CA) framework, GA is as the population space of CA and these two Algorithms are applied to the intelligent fixing test paper strategy research by combining. This method guides the population evolution efficiently through belief space and speeds up convergence. The experimental results prove that the algorithm keeps good average fitness and high operating efficiency.

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Method / approach

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Available abstract

According to the feature that genetic algorithm (GA) is adapted to requirement of culture algorithms (CA) framework, GA is as the population space of CA and these two Algorithms are applied to the intelligent fixing test paper strategy research by combining. This method guides the population evolution efficiently through belief space and speeds up convergence. The experimental results prove that the algorithm keeps good average fitness and high operating efficiency.

Key concepts: Algorithm, Cultural algorithm, Convergence (economics), Computer science, Genetic algorithm, Population, Population-based incremental learning, Algorithm design

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