We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Design of Intelligent Political Test Paper Generation Method Based on Improved Intelligent Optimization Algorithm.
- Authors
Qing Wan
- 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 test paper generation, 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 tdistribution 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.
- Subjects
OPTIMIZATION algorithms; REAL numbers; SECURITIES trading; POLITICAL philosophy; PARTICLE swarm optimization; POLITICAL doctrines
- Publication
EAI Endorsed Transactions on Scalable Information Systems, 2024, Vol 11, Issue 5, p1
- ISSN
2032-9407
- Publication type
Article
- DOI
10.4108/eetsis.5862