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Research on knowledge return Model based on Fuzzy Comprehensive genetic algorithm

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DOI: 10.23977/trance.2021.030206 | Downloads: 6 | Views: 1055

Author(s)

Sen Liu 1

Affiliation(s)

1 School of Artificial Intelligence, Wuhan Textile University, Wuhan 430200, China

Corresponding Author

Sen Liu

ABSTRACT

Higher education is very important to the current era. Having a healthy higher education system in each country is the key to education functioning the paperll. To assess the health status of the higher education system, the paper established an evaluation model based on a fuzzy comprehensive method. Based on the results, the paper proposed a policy entitled "Knowledge Back to Homeland" to improve the higher education system in these countries with poor educational systems. The paper firstly analyzed the data of five countries (i.e. the United States, China, Australia, Russia, and Brazil) for the past ten years. The paper used factor analysis to select and retain five factors that have the deepest impact on the health of higher education: cost of higher education, national government investment, values of the degree, equitability, and quality of education. The paper obtained the the paperights of the above factors adopted by the analytic hierarchy process, equal to [0.1225 0.2849 0.4555 0.0771 0.060]. Furtherly, the paper constructed a fuzzy comprehensive model for these 5 factors. The paper selected 3 countries (i.e. China, Russia, and Brazil) and collected data from their national statistical bureaus. In a percentile system to evaluate, China got 85.0012 points, Brazil got 78.7705 points and Russia 79.8585 points. So the paper chose Brazil with the lothe paperst score as the target country for the improvement. Finally, the paper conducted a sensitivity analysis, which indicated our model was stable for multiindex evaluation and also had high prediction accuracy.

KEYWORDS

Fuzzy synthesis, factor analysis, genetic algorithm, BP neural network, Markov model, policy

CITE THIS PAPER

Sen Liu, Research on knowledge return Model based on Fuzzy Comprehensive genetic algorithm. Transactions on Comparative Education (2021) Vol. 3: 33-37. DOI: http://dx.doi.org/10.23977/trance.2021.030206

REFERENCES

[1] Zheng Lei, “A Comparative study on the influencing factors of higher Education demand betthe paperen China and Foreign countries”, School of Economics and Business Administration, Beijing normal University, No. 9, 2008: 51-55 pages. 
[2] Jiang Qiyuan Xie Jinxing Ye Jun, “Mathematical Model (third Edition)”: higher Education Press, August 2003. 
[3] Li Xueshu, “Research Trends and Reflections on the influencing factors of Teaching quality in Foreign Universities”, Department of Development and Research, Shanghai Open University, 75-78 pages, August 6, 2000. 
[4] Xia Xiufang, “Construction and Application of Markov Model, Department of Finance and Economics”, Qingdao Institute of Architecture and Engineering, January 2020: 44-45 pages. 
[5] Tang Xiaoling, “Research on the Competitiveness of BRICS higher Education-- based on the comparison of data from Brazil”, Russia, India and China, Sichuan Foreign Studies University, Modern Education Management, No. 9, 2018: 123-128 pages.

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