Intelligent test paper method based on genetic particle swarm optimization algorithm

Abstract

The invention relates to an intelligent test paper method based on a genetic particle swarm optimization algorithm, comprising: generating the objective function corresponding to each constraint condition according to the constraint condition corresponding to test paper attribute information, and calculating the fitness function of test paper according to the objective function corresponding to each constraint condition; obtaining test questions from an item bank to form a plurality of pieces of test paper, and performing chromosome coding on each piece of test paper, wherein each piece of test paper corresponds to a chromosome, the chromosome includes a plurality of segments, each segment of chromosome corresponds to a type of test questions, and includes a plurality of genes, and each gene corresponds to a test question; obtaining an initial population through a particle swarm algorithm; and processing the initial population through a genetic algorithm to obtain a new population to output test paper therein. According to the technical scheme, the method employs test paper attribute information as constraint conditions to generate a fitness function, and performs particle swarm algorithm and genetic algorithm treatment on test paper according to the fitness function, thereby obtaining test paper meeting user needs.

Description

technical field [0001] The present invention relates to the technical field of intelligent examination papers, in particular to an intelligent examination paper formation method based on genetic particle swarm algorithm. Background technique [0002] Traditional paper assembly operations are almost entirely done manually, or semi-manually. Manual test paper composition is costly and has a high error rate, which is prone to omissions and unavoidable human factors, which often lead to unscientific and reasonable test paper composition. Although semi-manual examination paper composition partially reduces the workload of staff, key technical tasks such as selection and arrangement of test questions must still be completed manually, so there are still limitations and deficiencies such as low efficiency. [0003] In recent years, some scientific research institutions at home and abroad have developed some intelligent automatic paper composition systems. The methods used mainly in...

AI Technical Summary

Problems solved by technology

Although these methods can be used to achieve automatic examination paper formation to a certain extent, examination paper formation is a multi-objective optimization problem. Some of these methods are relatively simple; The actual needs; some test papers take up a lot of memory, the program structure is more complicated, and the test paper takes a long time

The limitations of these methods may cause the test papers generated by them to fail to meet the actual needs

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