Numerical analysis of p-vector norm errors in interacting data under random noise fluctuation
*Ogethakpo Arhonefe JosephCorresponding authorarhonefe@delsu.edu.ngDepartment of MathematicsDelta State UniversityAbraka, Nigeria0009-0004-6013-1341View full profile → , Ogoegbulem Oziomaozioma.ogoegbulem@dou.edu.ngDepartment of MathematicsDennis Osadebay UniversityAnwai, Asaba, Delta State, NigeriaView full profile → , Nwagor Peterspeter.nwagor@iaue.edu.ngDepartment of Mathematics and StatisticsIgnatius Ajuru University of EducationPort Harcourt, NigeriaView full profile → , Nwaigwe Chrysogonus Chinagoromnwaigwe.chrysogonus@dou.edu.ngDepartment of StatisticsFederal University of Technology OwerriDennis Osadebay UniversityAsaba, NigeriaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 May 2025
- Published Online:
- 03 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2177
- Pages:
- 1–18
Abstract
This study investigates the p-vector norm error between interacting datasets subjected to random noise fluctuations using a numerical simulation approach. A system of nonlinear ordinary differential equations was analyzed to quantify errors between controlled and uncontrolled data under a noise intensity of 0.2. The Runge-Kutta fourth-order (RK4) method was employed for numerical simulations, and steady-state solutions were derived for equilibrium points. The results demonstrated that the p-vector norm errors (D1, D2, D3, D4) followed a monotonically decreasing sequence, with D3 exhibiting the least error. This study provides a framework for selection, development and validation of the best model for prediction, highlighting the impact of random noise on statistical dispersion metrics such as range, mean, and variance.
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References
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