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Research on Statistical Characteristics Modeling of Matching Probability and Measurement Error Based on Machine Learning

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  • Shuan-zhu Li

    (Hebei Institiute of Communications, China)

  • Run-feng He

    (Liuzhou Railway Vocational Technical College, China)

  • Bao-zhu Pan

    (Hebei Polytechnic Institute, China)

Abstract

In view of the problems of the current modeling methods for the statistical characteristics of matching probability and measurement error, the modeling method of matching probability and measurement error statistical characteristics based on machine learning is proposed. According to the requirements of total sequence matching probability and system matching times, the sequence matching probability is calculated. The measurement error is analyzed in the process of acquisition and matching, and the measurable interference parameters are obtained. According to the analysis results, the mean value of matching measurement error is standardized, and the matching probability and measurement error statistical characteristics are established sex model. The experimental results show that the matching probability and measurement error statistical model of this method has high accuracy, and has good application effect in practical application.

Suggested Citation

  • Shuan-zhu Li & Run-feng He & Bao-zhu Pan, 2022. "Research on Statistical Characteristics Modeling of Matching Probability and Measurement Error Based on Machine Learning," International Journal of Information Systems in the Service Sector (IJISSS), IGI Global, vol. 14(2), pages 1-13, April.
    • Handle: RePEc:igg:jisss0:v:14:y:2022:i:2:p:1-13
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