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Intelligent Generating Test Paper Scheme for English Class Based on Genetic Algorithm
- Source :
- 2014 Sixth International Conference on Measuring Technology and Mechatronics Automation.
- Publication Year :
- 2014
- Publisher :
- IEEE, 2014.
-
Abstract
- This paper mainly discussed the implementation of genetic algorithm on generating test paper for English class. The existing genetic algorithm is optimized through the analysis on principles and key technologies of standard genetic algorithms. We use matrix encoding to improve the coding method. It can storage various properties of indicators and fitness of individual papers and improve computing speed. By the improvement of genetic operators, we propose a sectional multi-point strategy for mutation operator. A large proportion of hybridization and mutation are adopted to maintain the diversity of population, which avoid the knowledge conflict in generating paper and rapid shrinking when searching space. It also raises the speed of approximating to the global optimum and improves the comprehensive performance. Simultaneously, to ensure the best individual parent enter the offspring, we adopt the selection method based on fitness sorting during copy, to make the selection on the generation be the best strategy. The experiments results verify the effectiveness and practicality of our algorithm.
- Subjects :
- education.field_of_study
Fitness function
Computer science
Cultural algorithm
business.industry
Population
Quality control and genetic algorithms
Genetic operator
Machine learning
computer.software_genre
Fitness proportionate selection
Genetic algorithm
Artificial intelligence
Genetic representation
education
business
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2014 Sixth International Conference on Measuring Technology and Mechatronics Automation
- Accession number :
- edsair.doi...........3bd5c5b325c2361f1a482cf4bea828f4