基于广义正交模糊集和前景理论的区域学前教育发展水平测度与政策优化

Q2 Social Sciences
Qian Wang
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引用次数: 0

摘要

学前教育属于非义务启蒙教育,由于其属性的多重性和影响因素的多样性,很难对不同地区学前教育的发展进行衡量和分析。此外,决策者在面对多属性因素和不确定因素时,会受到自身认知的限制,给出的决策结果与实际情况存在较大差距。因此,本章将广义正交模糊集和前景理论引入到基于理想解相似度排序技术(TOPSIS)方法的学前教育发展水平测量模型中,以提高决策者的决策准确性。实验结果表明,该模型能有效处理不确定信息,提高分析精度,与其他模型相比,结果更符合实际情况。同时,它能直观地比较和分析不同地区学前教育的发展状况,为决策者提供可靠的数据支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measurement and Policy Optimization of Regional Preschool Education Development Level Based on Generalized Orthogonal Fuzzy Sets and Prospect Theory
Preschool education belongs to non-compulsory enlightenment education, and it is difficult to measure and analyze the development of preschool education in different regions because of its multiple attributes and diversity of influencing factors. In addition, decision makers will be limited by their own cognition when facing multi-attribute factors and uncertain factors, and there is a big gap between the decision results given and the actual situation. Therefore, this chapter introduces generalized orthogonal fuzzy sets and prospect theory into the measurement model of preschool education development level based on technique for order of preference by similarity to ideal solution (TOPSIS) method to improve the decision accuracy of decision makers. The experimental results show that the model can effectively deal with uncertain information and improve the analysis accuracy, and the results are more in line with the actual situation than other models. At the same time, it can intuitively compare and analyze the development of preschool education in different regions, and provide reliable data support for decision makers.
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CiteScore
2.40
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0.00%
发文量
68
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