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Evaluation and Prognostics of the Higher Education Based on Neural Network and AHP-PLS Structural Equations

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Data Science (ICPCSEE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1452))

Abstract

As a subsystem of society, higher education is an inevitable choice to meet the political and economic development of a country. Research of the higher education evaluation system is of great significance to the development of society. In this paper, a backpropagation (BP) neural network model is established to predict the future development scale of higher education. The analytic hierarchy process (AHP) method and partial least squares regression (PLS) structural equations were used to verify the scientificity and feasibility of the model. BP neural network has strong nonlinear mapping capabilities, and it is capable of the prognostics. It performed well on issues with more complicated internal mechanisms. Through experimental simulations, it is found that the BP neural network model has a good fit when making predictions and the relative error is less than 3%, which shows that the prediction results obtained with this model have high reliability.

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Authors and Affiliations

  1. School of Science, Harbin University of Science and Technology, Harbin, China

    Fanyueyang Zhang & Xianhua Song

  2. School of Economics and Management, Harbin University of Science and Technology, Harbin, China

    Xunbo Zhang

  3. School of Measurement and Control Technology and Communication Engineering, Harbin University of Science and Technology, Harbin, China

    Zirui Tang

Authors
  1. Fanyueyang Zhang
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  2. Xunbo Zhang
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  3. Zirui Tang
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  4. Xianhua Song
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Corresponding author

Correspondence to Xianhua Song .

Editor information

Editors and Affiliations

  1. North University of China, Taiyuan, China

    Jianchao Zeng

  2. North University of China, Taiyuan, China

    Pinle Qin

  3. Northeast Forestry University, Harbin, China

    Weipeng Jing

  4. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  5. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

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Zhang, F., Zhang, X., Tang, Z., Song, X. (2021). Evaluation and Prognostics of the Higher Education Based on Neural Network and AHP-PLS Structural Equations. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2021. Communications in Computer and Information Science, vol 1452. Springer, Singapore. https://doi.org/10.1007/978-981-16-5943-0_39

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  • DOI: https://doi.org/10.1007/978-981-16-5943-0_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5942-3

  • Online ISBN: 978-981-16-5943-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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