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Showing 1 - 20 results of 41 for search '(( (code OR mode) genetic algorithm ) OR ( image encryption algorithm ))', query time: 0.11s Refine Results
  1. 1

    A image encryption algorithm based on chaotic Lorenz system and novel primitive polynomial S-boxes by Temadher Alassiry Al-Maadeed (14147847)

    Published 2022
    “…<p>We have proposed a robust, secure and efficient image encryption algorithm based on chaotic maps and algebraic structure. …”
  2. 2

    A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer by M. Z. Yildiz (16855476)

    Published 2019
    “…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”
  3. 3

    A New Parallel Genetic Algorithm Model by Al-Somani, Turki F.

    Published 2020
    “…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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  4. 4

    A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group by Iqtadar Hussain (14147850)

    Published 2023
    “…To ensure the appropriate utilization of these chaotic maps, we carry out in-depth analyses of their behavior in the context of secure communication and apply the pseudo-random sequences of chaotic maps in the proposed image encryption algorithm accordingly.</p><h2>Other Information</h2><p dir="ltr">Published in: Computational and Applied Mathematics<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s40314-023-02208-x" target="_blank">https://dx.doi.org/10.1007/s40314-023-02208-x</a></p>…”
  5. 5

    A new genetic algorithm approach for unit commitment by Mantawy, A.H.

    Published 1997
    “…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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  6. 6

    Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems by Abdel Magid, Y.L.

    Published 2020
    “…The task of selecting the output feedback gains is converted to a simple optimization problem with an eigenvaluebased objective function, which is solved by a genetic algorithm. An objective function is presented allowing the selection of the output feedback gains to place the closed-loop eigenvalues in the left-hand side of a vertical line in the complex s-plane while shifting a specific mode of oscillation to a vertical strip and with bounds on the damping ratio. …”
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  7. 7

    A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

    Published 2000
    “…The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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  8. 8

    Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

    Published 2006
    “…The search space is too large to be explored by deterministic algorithms. In this paper, a Genetic Algorithm based algorithm for synthesis of MVL functions is proposed. …”
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    Design of PSS and STATCOM-based damping stabilizers using genetic algorithms by Abido, M.A.

    Published 2006
    “…The design problem of STATCOM-based stabilizers is formulated as an optimization problem. Then, a real-coded genetic algorithm (RCGA) is employed to search for optimal stabilizer parameters. …”
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  11. 11

    Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

    Published 1999
    “…A new implementation of the genetic algorithm is introduced. The genetic algorithm solution is coded as a mix between binary and decimal representation. …”
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    Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms by Abdel-Magid, Y. L.

    Published 2004
    “…The coordinated design problem of robust excitation and TCSC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. …”
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  14. 14

    Optimal multiobjective design of robust power system stabilizers using genetic algorithms by Abdel-Magid, Y.L.

    Published 2003
    “…A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. …”
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  15. 15

    A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

    Published 2020
    “…In the proposed algorithm, genetic algorithm solution is coded as a mix between binary and decimal representation. …”
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  16. 16

    Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

    Published 2020
    “…A new implementation of the genetic algorithm is introduced. The genetic algorithm solution is coded as a mix between binary and decimal representation. …”
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    article
  17. 17

    Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars by Abathar Al-Hamrani (16494884)

    Published 2023
    “…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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    Practical single node failure recovery using fractional repetition codes in data centers by Itani, May

    Published 2016
    “…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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