sis 24(5):

Research Article

Design of Intelligent Political Test Paper Generation Method Based on Improved Intelligent Optimization Algorithm

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  • @ARTICLE{10.4108/eetsis.5862,
        author={Qing Wan},
        title={Design of Intelligent Political Test Paper Generation Method Based on Improved Intelligent Optimization Algorithm},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={5},
        publisher={EAI},
        journal_a={SIS},
        year={2024},
        month={5},
        keywords={intelligent political test paper generation methods, stock market trading optimisation algorithms, Circle chaos mapping, adaptive t-distribution variation strategies},
        doi={10.4108/eetsis.5862}
    }
    
  • Qing Wan
    Year: 2024
    Design of Intelligent Political Test Paper Generation Method Based on Improved Intelligent Optimization Algorithm
    SIS
    EAI
    DOI: 10.4108/eetsis.5862
Qing Wan1,*
  • 1: Xinxiang College
*Contact email: 15936570912@139.com

Abstract

With the development of artificial intelligence, computer intelligent grouping, as a research hotspot of political ideology examination paper proposition, can greatly shorten the time of generating examination papers, reduce the human cost, reduce the human factor, and improve the quality of political ideology teaching evaluation. Aiming at the problem that the current political ideology examination paper-grouping strategy method easily falls into the local optimum, a kind of intelligent paper-grouping method for political ideology examination based on the improved stock market trading optimisation algorithm is proposed. Firstly, by analyzing the traditional steps of political thought grouping, according to the index genus of the grouping problem and the condition constraints, we construct the grouping model of political thought test questions; then, combining the segmented real number coding method and the fitness function, we use the securities market trading optimization algorithm based on the Circle chaotic mapping initialization strategy and adaptive t-distribution variability strategy to solve the grouping problem of the political thought test. The experimental results show that the method can effectively find the optimal strategy of political thought exam grouping, and the test questions have higher knowledge point coverage, moderate difficulty, and more stable performance.