Test question optimization algorithm based on dynamic particle swarm

A technology of particle swarm algorithm and optimization algorithm, which is applied in the field of examination system, can solve the problems that it is difficult to meet the requirements of epilogue examination, the workload is heavy, and the learning status and learning effect of each candidate cannot be truly reflected, so as to avoid It is difficult to maintain in the later period, realize the effect of intelligence, and avoid double calculation

Pending Publication Date: 2019-11-12
杜向然
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Problems solved by technology

At present, the development and maintenance of most of the examination systems are jointly completed by engineers and education experts, and each time the workload is huge, it is difficult for such a system to meet the requirements for the examination
Due to the huge amount of visits to the episodic learning mode, the amount of daily online learning and exams is also huge. If the exam system cannot be updated and improved in time, such an exam system will not be able to truly reflect the learning status and status of each candidate. Learning effect, for this reason, the present invention proposes a kind of test question optimization algorithm based on dynamic particle swarm

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  • Test question optimization algorithm based on dynamic particle swarm

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Embodiment Construction

[0029] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0030] see figure 1 , the present invention provides a technical solution: a test question optimization algorithm based on dynamic particle swarm optimization, the test question optimization algorithm includes algorithm initialization, evaluation functions in the optimization algorithm and global and local optimal values, specifically as follows:

[0031] ①Algorithm initialization: In the test question optimization algorithm based on dynamic particle swarms, each particle represents a set of parameters to be optimized (that is, the parameters of each test question in the test paper), and these parameters are represented by three-dimensional variables p=[p 111 ,p 112 ,p 113 ,...,p NSP ], where the parameter N represents the type of test question...

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Abstract

The invention provides a test question optimization algorithm based on a dynamic particle swarm. The test question optimization algorithm comprises algorithm initialization, an evaluation function inthe optimization algorithm and global and local optimal values. The test question optimization algorithm based on the dynamic particle swarm is reasonable in design, the parameter quality of test questions can be effectively improved, and then the accuracy of an evaluation function of an examination system is improved.

Description

technical field [0001] The invention belongs to the technical field of examination systems, in particular to a test question optimization algorithm based on dynamic particle swarms. Background technique [0002] In recent years, with the rapid development of big data and Internet technology, people's learning and examination patterns have undergone major changes, and online courses have become an important way for many people to acquire knowledge and skills. MOOK (MOOK) is one of the most influential online course models in the world. It was initiated by many famous universities around the world and provides a large number of high-quality online development courses. Students around the world can learn excellent courses from prestigious schools and share excellent educational resources without leaving home. In this non-face-to-face education method, it is particularly important to keep abreast of each student's learning status and information. An online examination system i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/15G06N3/00
CPCG06F17/15G06N3/006
Inventor 杜向然
Owner 杜向然
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