M. BOUDERAH Brahim

Prof

Directory of teachers

Department

Mathematics Department

Research Interests

Specialized in Mathematics Department. Focused on academic and scientific development.

Contact Info

University of M'Sila, Algeria

Email : brahim.bouderah@univ-msila.dz

On the Web:

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Recent Publications

2025-03-18

Homotopy Perturbation ρ-Laplace Transform Approach for Numerical Simulation of Fractional Navier-Stokes Equations

In this study, we tackle the time fractional discrete Navier-Stokes equation by employing the homotopyperturbation ρ-Laplace transform method (HPLTM), utilizing the Caputo-Katugampola fractional derivative of time.Additionally, we present graphical representations of the solution generated using Matlab software, comparing it withthe exact solution for α = 1. We perform two test problems to verify and demonstrate the effectiveness of our approach.Our numerical findings and graphical analyses indicate that the proposed approach exhibits remarkable efficiency andsimplicity, rendering it suitable for addressing a diverse array of challenges encountered in engineering and the sciences
Citation

M. BOUDERAH Brahim, Awatif Alghahtani, , (2025-03-18), "Homotopy Perturbation ρ-Laplace Transform Approach for Numerical Simulation of Fractional Navier-Stokes Equations", [international] Contemporary Mathematics , Universal Wiser Publisher

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2024-12-10

Parallel Association Rules Mining Using GPUs and Reptile Search Algorithm

This paper proposes a novel approach to accelerate association rule mining using the Reptile Search Algorithm (RSA) in conjunction with GPU-based parallel processing. Traditional association rule mining techniques can be computationally expensive, especially with large datasets. By utilizing the inherent parallelism of Graphics Processing Units (GPUs), we significantly speed up the fitness evaluation process, a core component of the Reptile Search Algorithm. Our results show a marked improvement in the performance of RSA on large datasets, making it feasible for real-time or large scale applications such as market basket analysis, healthcare for drug interaction analysis, and web usage mining. We also analyze the impact of various GPU optimizations and present a comparison with CPU-based execution.
Citation

M. BOUDERAH Brahim, kameleddine.heraguemi@univ-msila.dz, , (2024-12-10), "Parallel Association Rules Mining Using GPUs and Reptile Search Algorithm", [international] The Sixth International Symposium on Informatics and Its Applications (ISIA) , Université Mohamed Boudiaf M'Sila

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2024-06-01

Reptile Search Algorithm for Association Rule Mining

Association rule mining (ARM) is a very popular, engaging, and active research area in data mining. It seeks to find valuable
connections between different attributes in a defined dataset. ARM, which describes it as an NP-complete problem, creates a fertile field
for optimization applications. The Reptile Search Algorithm (RSA) is an innovative evolutionary algorithm. It yanks stimulation from
the encircling and hunting conducts of crocodiles. It is a well-known optimization technique for solving NP-complete issues. Since its
introduction by Abualigah et al. in 2022, the approach has attracted considerable attention from researchers and has extensively been
used to address diverse optimization issues in several disciplines. This is due to its satisfactory execution speed, efficient convergence
rate, and superior effectiveness compared to other widely recognized optimization methods. This paper suggests a new version of the
reptile search algorithm for resolving the association rules mining challenge. Our proposal inherits the trade-off between local and
global search optimization issues demonstrated by the Reptile search algorithm. To illustrate the power of our proposal, a sequence of
experiments is taken out on a varied, well-known, employing multiple comparison criteria. The results show an evident dominance of
the proposed approach in the front of the famous association rules mining algorithms as well as Bees Swarm Optimization (BSO), Bat
Algorithm (BA), Whale Optimization Algorithm (WOA), and others regarding CPU time, fitness criteria, and the quality of generated
rules.
Citation

M. BOUDERAH Brahim, kameleddine.heraguemi@univ-msila.dz, , (2024-06-01), "Reptile Search Algorithm for Association Rule Mining", [national] International Journal of Computing and Digital Systems , University of Bahrain

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