Affiliations: [a] College of Business Administration, Capital University of Economics and Business, Beijing, China
| [b] Sinopec Shanghai SECCO Petrochemical Company Limited, Shanghai, China
Correspondence:
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Corresponding author. Kong Haining, College of Business Administration, Capital University of Economics and Business, 100026 Beijing, China. E-mail: konghaining@126.com.
Abstract: Teaching quality evaluation is important to improve teaching quality in universities. Fuzzy comprehensive evaluation is a comprehensive method of qualitative analysis and quantitative analysis. It has been widely applied in social life, economic management and engineering technology. The scientific practice has proved that the rational distribution of the weight factors and the selection of the evaluation model directly affect the accuracy and reliability of the fuzzy comprehensive evaluation results. How to determine the weight of multiple indicators into a single index is the focus of the present study. The simulation results show that the parameters of the gaussian kernel function optimization method designed in this article has strong advantages. Also, the results show that the algorithm presented in this paper can accurately reflect the quality of teaching quality, and at the same time realize the accurate determination of the weight of teaching quality evaluation index.
Keywords: Support vector machine, big data analytics, gaussian kernel function, teaching quality evaluation, parameter optimization
