<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>We use the Legendre wavelet method to study nonlinear fractional differential equations. Based on the in-depth study of the characteristics of various fractional-order dynamic system models, this paper designs a system for solving fractional-order differential equations, and we apply them to the anomaly analysis of big computer data. This method can improve the efficiency of big data classification. The results of computer numerical simulation show that the designed algorithm for solving fractional differential equations has high accuracy. At the same time, the algorithm can avoid misclassification and omission in big data analysis.</p>
</abstract>

We use the Legendre wavelet method to study nonlinear fractional differential equations. Based on the in-depth study of the characteristics of various fractional-order dynamic system models, this paper designs a system for solving fractional-order differential equations, and we apply them to the anomaly analysis of big computer data. This method can improve the efficiency of big data classification. The results of computer numerical simulation show that the designed algorithm for solving fractional differential equations has high accuracy. At the same time, the algorithm can avoid misclassification and omission in big data analysis.

Abnormal Behavior of Fractional Differential Equations in Processing Computer Big Data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

We use the Legendre wavelet method to study nonlinear fractional differential equations. Based on the in-depth study of the characteristics of various...

Abnormal Behavior of Fractional Differential Equations in Processing Computer Big Data

Online veröffentlicht: 06. Juni 2023

Seitenbereich: 291 - 298

Eingereicht: 18. Jan. 2022

Akzeptiert: 27. März 2022

DOI: https://doi.org/10.2478/amns.2022.2.00011

Schlüsselwörter
Partial differential classification, Mathematical model, Improvement of association mining, Minimum feature vector

© 2023 Jianjie Ding et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Abnormal Behavior of Fractional Differential Equations in Processing Computer Big Data

Online veröffentlicht: 06. Juni 2023

Seitenbereich: 291 - 298

Eingereicht: 18. Jan. 2022

Akzeptiert: 27. März 2022

DOI: https://doi.org/10.2478/amns.2022.2.00011

SchlüsselwörterPartial differential classification, Mathematical model, Improvement of association mining, Minimum feature vector

© 2023 Jianjie Ding et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Partial differential classification, Mathematical model, Improvement of association mining, Minimum feature vector