Search alternatives:
based function » taste function (Expand Search)
value function » taste function (Expand Search)
algorithm both » algorithm goa (Expand Search), algorithm aoa (Expand Search), algorithm its (Expand Search)
both function » cost function (Expand Search)
Showing 1 - 9 results of 9 for search '(((( algorithm based function ) OR ( algorithm value function ))) OR ( algorithm both function ))~', query time: 0.09s Refine Results
  1. 1
    Cross entropy error function in neural networks

    Cross entropy error function in neural networks by Nasr, G.E.

    Published 2002
    “…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
    Get full text
    Get full text
    Get full text
    conferenceObject
    Save to List
    Saved in:
  2. 2
    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems

    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…The local search operator employs a single insertion approach, while the acceptance–rejection criteria are based on a constant temperature. Parameters of both ES and IG algorithms are calibrated using the Multifactor analysis of variance technique. …”
    Save to List
    Saved in:
  3. 3
    Genetic and heuristic algorithms for regrouping service sites. (c2000)

    Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

    Published 2000
    Get full text
    Get full text
    masterThesis
    Save to List
    Saved in:
  4. 4
    New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications

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

    Published 2019
    “…The new algorithm exploits the pseudo-linear region around the tangent function zero point to estimate a reduced input arctangent through a modified rational approximation before referring this estimate to its original value using miniature LUTs. …”
    Save to List
    Saved in:
  5. 5
    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
    Get full text
    Save to List
    Saved in:
  6. 6
    On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network

    On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)

    Published 2020
    Save to List
    Saved in:
  7. 7
    A Dual Vibration Absorber for Vibration Suppression of Harmonically Forced Systems

    A Dual Vibration Absorber for Vibration Suppression of Harmonically Forced Systems by El Khoury, Elie

    Published 2022
    “…Then, a numerical technique based on both the genetic algorithm and the search simplex method is used to calculate the optimal system parameters. …”
    Get full text
    Get full text
    Get full text
    masterThesis
    Save to List
    Saved in:
  8. 8
    Iterative heuristics for multiobjective VLSI standard cellplacement

    Iterative heuristics for multiobjective VLSI standard cellplacement by Sait, Sadiq M.

    Published 2001
    “…We employ two iterative heuristics for the optimization of VLSI standard cell placement. These heuristics are based on genetic algorithms (GA) and tabu search (TS) respectively. …”
    Get full text
    Get full text
    article
    Save to List
    Saved in:
  9. 9
    Intelligent Bilateral Client Selection in Federated Learning Using Game Theory

    Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

    Published 2022
    “…Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
    Get full text
    Get full text
    Get full text
    masterThesis
    Save to List
    Saved in:

Search Tools: