원문정보
보안공학연구지원센터(IJMUE)
International Journal of Multimedia and Ubiquitous Engineering
Vol.9 No.11
2014.11
pp.255-264
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
The paper presents an evolution of personalized courses based on genetic algorithms (PCEGA). The genetic algorithm are successfully applied in the dynamic update process of the course during the whole learning process. Under this framework of this algorithm, the target user model updates dynamically, and the courses evolve during the process. It provides a good general purpose and scalable framework that addresses the personalized course generation in an online learning environment.
목차
Abstract
1. Introduction
2. Realization of Personalized Course Generation and Evolution Based on Genetic Algorithm (PCEGA)
2.1. Gene Metadata
2.2. The Algorithm Flow
2.3. Realization of PCEGA Algorithm
3. Experiment Design and Discussion
3.1. Determining the Crossover Probability and Mutation Probability
3.2. Determining the Choice of Operator
3.3. Determining the Crossover Operator
4. Conclusion
References
1. Introduction
2. Realization of Personalized Course Generation and Evolution Based on Genetic Algorithm (PCEGA)
2.1. Gene Metadata
2.2. The Algorithm Flow
2.3. Realization of PCEGA Algorithm
3. Experiment Design and Discussion
3.1. Determining the Crossover Probability and Mutation Probability
3.2. Determining the Choice of Operator
3.3. Determining the Crossover Operator
4. Conclusion
References
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자료제공 : 네이버학술정보