Showing 1 - 20 results of 276 for search '(( time processing algorithm ) OR ((( element data algorithm ) OR ( agent based algorithm ))))*', query time: 0.13s Refine Results
  1. 1
  2. 2
  3. 3

    Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

    Published 2023
    “…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
  4. 4
  5. 5

    New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications by Mohieddine Benammar (18103039)

    Published 2019
    “…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. …”
  6. 6
  7. 7

    Agent-Based Reactive Geographic Routing Protocol for Internet of Vehicles by Mazouzi, Mohamed

    Published 2023
    “…In this paper, we first propose a novel lightweight location service that permits to discover all the geographical paths between two vehicles based on smart mobile agents. Second, we proposed ARGENT an Agent-Based Reactive Geographic Routing Protocol that couples the routing process with the novel lightweight location service. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  8. 8
  9. 9

    ARDENT: A Proactive Agent-Based Routing Protocol for Internet of Vehicles by Mazouzi, Mohamed

    Published 2023
    “…Then, we present an Agent-Based Proactive Geographic Routing Protocol called ARDENT to route data packets with reduced delay and higher delivery ratio. …”
    Get full text
    Get full text
    Get full text
    Get full text
    article
  10. 10
  11. 11

    Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

    Published 2024
    “…<p>This paper introduces a novel approach to solve the coverage optimization problem in multi-agent systems. The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. …”
  12. 12

    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

    Published 2021
    “…The objective is to minimize different cost types while satisfying constraints such as resources availability, customer service level, and tasks dependency relation. The algorithm proved its effectiveness by allocating tasks with higher priority and weight while taking into consideration customers’ Service Level Agreement, time, and different types of costs, which led to a lower total cost of the batching process. …”
    Get full text
    article
  13. 13
  14. 14

    Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

    Published 2023
    “…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …”
    Get full text
  15. 15

    A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

    Published 2023
    “…It is found that the useful features hidden in the time domain are highlighted when the audio signal is converted to a spectrogram, which can be treated as an image. …”
  16. 16
  17. 17
  18. 18

    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
  19. 19
  20. 20