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Network monitoring and processing accuracy of big data acquisition based on mathematical model of fractional differential equation

Applied Mathematics and Nonlinear Sciences, ISSN: 2444-8656, Vol: 7, Issue: 2, Page: 327-340
2022
  • 1
    Citations
  • 0
    Usage
  • 11
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1
  • Captures
    11
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

New Findings from Teachers College in the Area of Data Acquisition Described (Network monitoring and processing accuracy of big data acquisition based on mathematical model of fractional differential equation)

2023 FEB 20 (NewsRx) -- By a News Reporter-Staff News Editor at Network Daily News -- Research findings on data acquisition are discussed in a

Article Description

Aiming at the lack of subjectivity of the network security situation assessment method and the complexity and non-linearity of data obtained through situational factors, a fuzzy neural network security situation which is optimised based on an improved gravitational search algorithm combined with fractional differential equation analysis, as an Evaluation model, is proposed. In order to quickly and accurately predict the situation value of the network security situation at that moment, a method for situation prediction of long-term and short-term memory networks based on an improved Nadam algorithm to optimise the online update mechanism is proposed. Note that the situation time series obtained from online assessment cannot be used in a better and efficient manner. The model can minimise the cost function and update the model more effectively by updating the model parameters online Prediction accuracy. In order to improve the problem of slow convergence speed during model network training, the Look-ahead method is used to improve Nesterov's adaptive gradient momentum estimation algorithm to accelerate the model's convergence. Finally, the simulation results analyse and compare the prediction model, which not only improves the convergence speed of the prediction model, but also greatly reduces the prediction error of the model.

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