Online Self-Test System Grouping Function of Genetic Algorithm-Based Optimization

Abstract:

The paper mainly discusses the genetic algorithm to optimize the test paper module and Research and Implementation of online self-test system. Online self-test characteristics of the system, coding, crossover and mutation improvement on traditional genetic algorithm. Experimental results show that, the improved genetic algorithm has better performance than the conventional genetic algorithm, improves the efficiency of solving the quality of test paper and issues, promotes a more widely used online self-testing system in the field of education.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 2776-2780
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.2776
• Online since: August 2013
• Authors: Li Ping Zhang, Da Shen Xue
• Keywords: Algorithm (GA), Function Test Paper, Online Self-Test System

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