Computer Intelligent Test Paper System Based on Genetic Algorithm

Abstract

The rapid development of the Internet has brought tremendous changes to people’s lives. Through the network function, the online examination is gradually accepted by various educational and teaching institutions. Currently, online exams have become the main method of teaching evaluation. In order to solve the problem of intelligent test paper more effectively, this paper proposes a mufti-threaded intelligent test paper strategy based on genetic algorithm, and designs the computer system structure in the standard test question bank. Convergence simulation and experimental results show that the algorithm is better than simple particle swarm optimization algorithm, simple genetic algorithm and its improved algorithm. Established a mathematical model and objective function for test paper composition, and proposed an intelligent test paper composition strategy based on genetic algorithm. The investigator used overall coding, crossover and mutation operations to improve the global optimization capability and convergence speed. It overcomes the phenomenon of premature and improves the accuracy and speed of convergence. It has the advantages of strong optimization ability and good stability.