Browsing by Author "Mehenni, Tahar: Supervisor"

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    Clustering of urban taxi trajectory networks Case study: City of M’sila
    (Mohamed Boudiaf University of M'sila, 2024) Amrouche, Soulaf; Ben djenidi, Faiza; Mehenni, Tahar: Supervisor
    The goal of the graduation project presented in this report is to design and implementing a website whose use focuses on analyzing urban taxi routes in the city of M’sila using clustering techniques to improve taxi routes, reduce travel time, and improve service efficiency. In addition to the educational aspect, Website operations were developed in three stages: Analysis stage the problem, collecting sufficient information about the topic, and formulating this information To UML diagrams, the third stage of programming.
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    Prediction Model for Forests Fire Spread in M’sila
    (UNIVERSITY OF MOHAMED BOUDIAF - MSILA, 2023-06) Bechere, M’hamed Ayoub; Zamit, Zohir; Mehenni, Tahar: Supervisor
    In this study, three machine-learning algorithms (Linear regression, Polynomial Regression, and Random Forest Regression) were explored for predicting forest fires spread. A comprehensive dataset consisting of environmental and weather factors influencing forest fires was collected and used to train and test the models. Performance metrics such as accuracy, precision and recall score were used to evaluate the models. The results showed that all three algorithms performed well, but the Polynomial Regression Model achieved the highest accuracy. This study emphasizes the effectiveness of machine learning in forest fire spread prediction, particularly the superiority of the Polynomial Regression Model, and highlights the importance of leveraging advanced techniques for mitigating the impact of forest fires and protecting ecosystems