IMPROVING α-PARAMETERIZED DIFFERENTIAL TRANSFORM METHOD WITH DANDELION OPTIMIZER FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS

In this manuscript, we aim to address Ordinary Differential Equations (ODEs) by α-Parameterized Differential Transform Method (α-PDTM). Additionally, we seek to enhance the effectiveness of α-PDTM by incorporating the Dandelion Optimizer (DO). The DO plays a crucial role in optimizing the parameter α, ensuring its adjustment and modification to secure the most favorable value. This refinement results in a more accurate approximation compared to conventional methods. The proposed approach, referred to as (αDO-PDTM), demonstrates a solution distinguished by its reliability and efficiency, as determined through the computation of Maximum Absolute Error (MAE) and the Mean Square Errors (MSE).

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Publication Details

Journal
Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
Published
2024-12-21
DOI
https://doi.org/10.35784/iapgos.6363
Citations
1
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.35
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article

IMPROVING α-PARAMETERIZED DIFFERENTIAL TRANSFORM METHOD WITH DANDELION OPTIMIZER FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS

Omar Saber Qasim, Mustafa Raed Najeeb
1 citations
Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
Metaheuristic Optimization Algorithms Research
0.35
article

IMPROVING α-PARAMETERIZED DIFFERENTIAL TRANSFORM METHOD WITH DANDELION OPTIMIZER FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS

Omar Saber Qasim, Mustafa Raed Najeeb
article en
1 citations

Abstract

In this manuscript, we aim to address Ordinary Differential Equations (ODEs) by α-Parameterized Differential Transform Method (α-PDTM). Additionally, we seek to enhance the effectiveness of α-PDTM by incorporating the Dandelion Optimizer (DO). The DO plays a crucial role in optimizing the parameter α, ensuring its adjustment and modification to secure the most favorable value. This refinement results in a more accurate approximation compared to conventional methods. The proposed approach, referred to as (αDO-PDTM), demonstrates a solution distinguished by its reliability and efficiency, as determined through the computation of Maximum Absolute Error (MAE) and the Mean Square Errors (MSE).

Informatyka Automatyka Pomiary w Gospodarce i Ochronie ŚrodowiskaVol. 14(4)
University of Mosul (IQ)
Openalex Percentile: Top 30%
Metaheuristic Optimization Algorithms Research
0.35
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