Abstract
Objectives: In recent years, with the continuous improvement of the requirements of student training quality, the evaluation results of the existing evaluation system of student training quality are mostly unsatisfactory. Therefore, by integrating c-mean algorithm and Kohonen clustering algorithm, a non-sequential artificial neural network is obtained, a student training quality evaluation system based on KOHONEN neural network is designed by automatically adjusting the size of the objective function nodes of the non-sequential artificial neural network. Then the evaluation system is applied to the expected evaluation of the training quality of students in two science classes of Xinghua Middle School in Shenyang, Liaoning Province. The comparison between the test result data and the expected results of the model after the experiment confirms that the evaluation results obtained by using the evaluation system based on KOHONEN neural network have high accuracy.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.