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Quantitative Evaluation of NDE Reliability Based on Back Propagation Neural Network and Fuzzy Comprehensive Evaluation

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Abstract

There are some problems in the quality evaluation of network distance education, such as the large error in the quantitative results of the evaluation indicators, the low accuracy of the quality evaluation and the large error in the indicator's weight distribution. Therefore, a quantitative evaluation method of NDE reliability based on Back Propagation (BP) neural networks and fuzzy comprehensive evaluation is proposed. From the perspective of students, teachers and schools, the primary and secondary indicators of teaching evaluation are constructed, and the reliability evaluation indicators system of teaching quality is established. The fuzzy comprehensive evaluation method is used to calculate the membership degree of the evaluation indicators, the consistency verification method is used to determine the consistency of the indicator's attributes, and the quantitative research of the indicators data is completed by the weight calculation method to improve the accuracy of the quantitative results. BP neural network is used to construct the input layer, hidden layer and output layer of network distance education quality reliability evaluation indicators, calculate the weight of evaluation indicators, transform the input evaluation indicators data through linear conversion function, construct the indicators evaluation model, and correct the evaluation results with the help of loss function to improve the accuracy of quality evaluation results. The experimental results show that the evaluation result error of the proposed method is relatively small, with an error of less than 0.3%, and the highest evaluation accuracy reaches 96.3%, which can effectively improve the quantitative evaluation effect of the reliability of network remote teaching quality.

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Acknowledgements

This work was funded by Researchers Supporting Project number (RSPD2023R636), King Saud University, Riyadh, Saudi Arabia.

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Authors and Affiliations

  1. School of Smart Education, Jiangsu Normal University, Xuzhou, 211135, China

    Xiao Liu

  2. Department of Math and Computer Science, Brandon University, Brandon, Canada

    Gautam Srivastava

  3. Research Centre for Interneural Computing, China Medical University, Taichung, Taiwan

    Gautam Srivastava

  4. Department of Computer Science and Math, Lebanese American University, Beirut, Lebanon

    Gautam Srivastava

  5. Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, P.O.Box 51178, 11543, Riyadh, Saudi Arabia

    Maazen Alsabaan

Authors
  1. Xiao Liu
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  2. Gautam Srivastava
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  3. Maazen Alsabaan
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Corresponding author

Correspondence to Gautam Srivastava.

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The authors have no relevant financial or non-financial interests to disclose. Xiao Liu provided the algorithm and experimental results and wrote the manuscript, Gautam Srivastava discussed the direction, supervised and analyzed the experiment, and Maazen Alsabaan provided the experiment environment and revised the manuscript. We also declare that data availability and ethics approval does not apply to this paper.

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Liu, X., Srivastava, G. & Alsabaan, M. Quantitative Evaluation of NDE Reliability Based on Back Propagation Neural Network and Fuzzy Comprehensive Evaluation. Mobile Netw Appl 28, 914–923 (2023). https://doi.org/10.1007/s11036-023-02188-6

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  • DOI: https://doi.org/10.1007/s11036-023-02188-6

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