University of Bordj Bou Arreridj
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- كلية الحقوق والعلوم السياسية
- كلية الآداب واللغات
- كلية الرياضيات و الأعلام الآلي
- كلية علوم الطبيعة و الحياة و علوم الأرض و الكون
- كلية العلوم الاقتصادية والتجارية وعلوم التسيير
- Faculté des sciences et de la technologie
- كلية العلوم الاجتماعية والإنسانية
Recent Submissions
Agrinity - Smart Agriculture System
(Université Mohamed El Bachir El Ibrahimi B.B.A., 2025) SAID HADDAD abdel hakim; NOUIOUA djamel eddine islem
Abstract
This project presents the design and implementation of a Smart Agriculture System aimed
at improving agricultural efficiency through the integration of hydroponic cultivation, IoT technologies,
and Operations Research (OR) methods. Using a mobile application connected to an
ESP32 microcontroller, the system enables real-time monitoring and control of key environmental
parameters such as pH, temperature, water level, and irrigation cycles. The goal is to
maximize crop yield while minimizing resource consumption (water, energy, fertilizers).This
smart agriculture solution offers a replicable, scalable, and eco-friendly alternative to conventional
farming, paving the way for future developments in precision agriculture in Algeria and
similar environments.
Intelligent algorithms for feature selection in supervised and unsupervised classification
(University of Mohamed El Bachir El Ibrahimi - Bordj Bou Arréridj, 2026) Khaoula Zineb Legoui
The growing availability of high-dimensional datasets across various domains has made feature selection
a critical step in machine learning pipelines, as reducing irrelevant or redundant features enhances model
interpretability and generalization. Due to the combinatorial nature of feature selection, traditional meth
ods often lack the scalability and adaptability required for real-world problems. In response, this thesis
investigates the application of intelligent metaheuristic algorithms to feature selection in both supervised
and unsupervised learning settings. First, a comparative analysis of the Equilibrium Optimizer (EO) and
Henry Gas Solubility Optimization (HGSO) algorithms is conducted for supervised classification tasks. Both
algorithms are adapted to a binary feature space and evaluated on benchmark datasets using classification
accuracy and feature reduction as performance criteria, highlighting their respective strengths and motivat
ing a hybrid approach. Consequently, this thesis proposes HGSOEO, a hybrid algorithm that integrates the
complementary exploration and exploitation capabilities of HGSO and EO. The proposed HGSOEO algo
rithm is evaluated on the Twitter Spam Detection dataset and demonstrates superior performance in terms
of classification accuracy and the number of selected features when compared to conventional metaheuristic
and classical feature selection methods. Furthermore, the application of EO is extended to feature selection
for clustering tasks, where labeled data are unavailable, by employing clustering validity criteria such as the
Adjusted Rand Index (ARI) to guide the selection process. Experimental results across multiple datasets
confirm the effectiveness and robustness of the proposed approaches. Overall, the findings of this thesis
demonstrate that intelligent metaheuristic algorithms provide efficient and scalable solutions to the feature
selection problem in both supervised and unsupervised learning contexts.
Étude empirique entre les algorithmes heuristiques et métaheuristiques pour le Problème du Voyageur de Commerce
(Université Mohamed El Bachir El Ibrahimi B.B.A., 2025) Boumerta Maram; Messadek Aicha
This thesis analyzes heuristic and metaheuristic methods to solve the Traveling Salesman
Problem (TSP), comparing their efficiency in terms of speed, solution quality, and complexity.
It highlights the strengths and limitations of each approach, showing that heuristics like Clarke
and Wright and 2-opt offer a good balance between speed and precision. Finally, the study
emphasizes the
دور التمويل الإسلامي في رفع الكفاءة التمويلية لمشاريع الصناعات الغذائية تجارب دولية وسبل الاستفادة منها
(جامعة محمد البشير الإبراهيمي كلية العلوم الاقتصادية والتجارية وعلوم التسيير, 2026-01-07) بوبترة فارس
مدخل إلى علم اجتماع المنظمات
(2026-01) ترايكية يامنة