Mzedawee, Asaad Naser Hussein
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Optimization Algorithms for Enhanced Parameter Estimation in Mathematical Modelling Hasan, Ahmed; Mzedawee, Asaad Naser Hussein; Alsharify, Fouad Hamza Abd
Indonesian Journal of Mathematics and Applications Vol. 2 No. 1 (2024): Indonesian Journal of Mathematics and Applications (IJMA)
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ijma.2024.002.01.3

Abstract

Identifying optimization algorithms for parameter estimation is an important consideration in the dynamic landscape of computational science and mathematical modeling. This paper explores the complex relationship between mathematical models and optimization techniques, providing a comprehensive analysis of synergies a lies between them for they were established in order search. Our study attempted to shed light on its role in theoretical and practical terms: three important factors: perception, meeting behavior, and mathematical efficiency. In doing so, we found valuable insights into the art of algorithm selection, which provided useful insights into improving the accuracy and efficiency of mathematical models. Based on the presented results, the Powell optimization algorithm emerged as an outstanding tool, and model and algorithm continued to demonstrate multiple applicability in various sampling scenarios. By revealing complex interconnections, this study contributes to a growing discourse about mathematical modeling and optimization, and equips scientists, engineers, and decision-makers with the tools needed to meet complex real-world challenges with confidence and accuracy. Finally, the numerical results of the optimization show the superiority of Powell's algorithm in reaching the optimal solution and demonstrated its ability to deal with a wide range of scenarios.
Optimization Algorithms for Enhanced Parameter Estimation in Mathematical Modelling Hasan, Ahmed; Mzedawee, Asaad Naser Hussein; Alsharify, Fouad Hamza Abd
Indonesian Journal of Mathematics and Applications Vol. 2 No. 1 (2024): Indonesian Journal of Mathematics and Applications
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ijma.2024.002.01.3

Abstract

Identifying optimization algorithms for parameter estimation is an important consideration in the dynamic landscape of computational science and mathematical modeling. This paper explores the complex relationship between mathematical models and optimization techniques, providing a comprehensive analysis of synergies a lies between them for they were established in order search. Our study attempted to shed light on its role in theoretical and practical terms: three important factors: perception, meeting behavior, and mathematical efficiency. In doing so, we found valuable insights into the art of algorithm selection, which provided useful insights into improving the accuracy and efficiency of mathematical models. Based on the presented results, the Powell optimization algorithm emerged as an outstanding tool, and model and algorithm continued to demonstrate multiple applicability in various sampling scenarios. By revealing complex interconnections, this study contributes to a growing discourse about mathematical modeling and optimization, and equips scientists, engineers, and decision-makers with the tools needed to meet complex real-world challenges with confidence and accuracy. Finally, the numerical results of the optimization show the superiority of Powell's algorithm in reaching the optimal solution and demonstrated its ability to deal with a wide range of scenarios.