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Preschool Education Resource Allocation Model for Index System Evaluation Based on Nonlinear Random Matrix

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  • Jun Huang
  • Ning Cao

Abstract

Based on random finite sets and random matrices, this paper conducts research on ETT methods, focusing on solving key problems such as measurement set division, hybrid reduction, and target shape modeling, and provides theoretical and methodological support for ETT applications in complex environments. Evaluation is an activity to determine value, which is to judge the degree to which the object meets the requirements of the subject, that is, to judge against certain standards. Usually, the evaluation needs to go through a series of qualitative and quantitative combination; that is, subjective materials and objective statistical data are used together to judge and analyze to obtain the final evaluation result. The evaluation of preschool education resource allocation refers to qualitative and quantitative description of the relevant material and financial and human resources invested in the development of preschool education. This paper will study the preschool education resource allocation evaluation system from the aspect of the index system of the preschool education resource allocation evaluation system. The research results show that the average technical efficiency of preschool education resource allocation from 2019 to 2021 will increase steadily, and the combination of input elements in educational resources will be reasonable. In 2021, Spearman’s rho and Kendall’s tau correlation coefficients between overall technical efficiency and pure technical efficiency are as high as 0.958 and 0.841, which are higher than the correlation coefficients of 0.325 and 0.380 between overall technical efficiency and scale efficiency.

Suggested Citation

  • Jun Huang & Ning Cao, 2022. "Preschool Education Resource Allocation Model for Index System Evaluation Based on Nonlinear Random Matrix," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, August.
  • Handle: RePEc:hin:jnlmpe:6271690
    DOI: 10.1155/2022/6271690
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