2022年 06期

摘要(Abstract)：

针对当前质量评估模型精度低、可靠性差和效率不高的问题，提出一种基于烟花算法优化k均值聚类的教学质量评估模型；利用具有平衡全局和局部搜索能力的烟花算法对k均值聚类算法进行优化，将获得的数据结果作为k均值聚类算法的初始聚类中心点，解决k均值聚类算法容易陷入局部最优问题，分别从精度和建模时间2个方面验证所提出模型的评估性能。结果表明，所提出的模型对不同课程的评估精度均大于92%,评估结果可靠性较高，建模平均时间小于32.1 ms,效率较高。

关键词(KeyWords)： 教学质量评估;烟花算法;k均值聚类;局部最优

基金项目(Foundation): 国家自然科学基金项目(31971036,61871204);; 山东省本科教学改革研究项目(M2020327);; 教育部产学合作协同育人项目(202002030019)

作者(Author): 巨金香,张福泉,黄锐

DOI: 10.13349/j.cnki.jdxbn.20220920.002

参考文献(References)：

[1] 陈翔，韩响玲，王洋，等.课程教学质量评价体系重构与“金课”建设[J].中国大学教学，2019(5):43-48.

[2] SHEN X J,ZHANG J T,SHI X J,et al.Evaluation of teaching quality in colleges and universities based on adaptive BP neural network model[C]//2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS),November 23-25,2018,Nanjing,China.New York:IEEE,2018:752-756.

[3] XIONG C,DAI P.Research on the project teaching evaluation model based on AHP[C]//2018 13th International Conference on Computer Science & Education (ICCSE),August 8-11,2018,Colombo,Sri Lanka.New York:IEEE,2018:1-4.

[4] HUANG L P.Design of foreign language teachers’ teaching language teaching evaluation model based on association mining[C]//2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS),August 10-11,2018,Changsha,China.New York:IEEE,2018:375-378.

[5] QIN F,ZENG W J,LI L et al.Research on the evaluation model of university nuclear-driven teaching quality under double first-class background[C]//2020 International Conference on Big Data and Informatization Education (ICBDIE),April 23-25,2020,Zhangjiajie,China.New York:IEEE,2020:342-345.

[6] 李召召，王立德，岳川，等.基于MKLSVM的MVB端接故障诊断[J].北京交通大学学报，2019,43(2):100-106.

[7] YANG N,KONG D H.The research of teaching quality evaluation model based on the principal component analysis and learning vector quantization[C]//2020 International Conference on Artificial Intelligence and Education (ICAIE),June 26-28,2020,Tianjin,China.New York:IEEE,2020:79-84.

[8] QIAN Z H,HU C H.Optimal path selection for fault repair based on grid GIS platform and improved fireworks algorithm[C]//2019 IEEE 3rd Information Technology,Networking,Electronic and Automation Control Conference (ITNEC),March 15-17,2019,Chengdu,China.New York:IEEE,2019:2452-2456.

[9] SHI Y T,YAN Y H,LIU Y.Research on optimized reconfiguration of distribution network based on improved fireworks algorithm[C]//2020 5th Asia Conference on Power and Electrical Engineering (ACPEE),June 4-7,2020,Chengdu,China.New York:IEEE,2020:70-74.

[10] XU H,YAO S Y,LI Q Y,et al.An improved K-means clustering algorithm[C]//2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS),September 17-18,2020,Dortmound,Germany.New York:IEEE,2020.DOI:10.1109/IDAACS-SWS50031.2020.9297060.

[11] PUGAZHENTHI,KUMAR L S.Selection of optimal number of clusters and centroids for K-means and fuzzy c-means clustering:a review[C]//2020 5th International Conference on Computing,Communication and Security (ICCCS),October 14-16,2020,Patna,India.New York:IEEE,2020.DOI:10.1109/ICCCS49678.2020.9276978.

[12] ILHAM A,IBRAHIM D,ASSAFFAT L,et al.Tackling initial centroid of K-means with distance part (DP-KMeans)[C]//2018 International Symposium on Advanced Intelligent Informatics (SAIN),August 29-30,2018,Yogyakarta,Indonesia.New York:IEEE,2018:185-189.

[13] MacQUEEN J.Some methods for classification and analysis of multivariate observation[C]//Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability:Vol I:Statistics.California:University of California Press,1967:281-297.

[14] KAZANIDIS I,VALSAMIDIS S,GOUBOPOULOS E,et al.Proposed S-Algo+data mining algorithm for web platforms course content and usage evaluation[J].Soft Computing,2020,24(19):14861-14883.

[15] XIE R,LIU R,LIU X B,et al.Evaluation of SMEs’ credit decision based on support vector machine-logistics regression[J].Journal of Mathematics,2021,2021:5541436.