Showing 1 - 20 results of 351 for search '(((( algorithm from function ) OR ( algorithm l function ))) OR ( algorithm a function ))', query time: 0.15s Refine Results
  1. 1

    Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

    Published 2023
    “…Recently, optimization problems have been revised in many domains, and they need powerful search methods to address them. In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
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  2. 2

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

    Published 1997
    “…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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  3. 3

    Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

    Published 2022
    “…The constructed Ls-AOA algorithm was then proposed to design a proportional-integral-derivative (PID) controller employed in a functional electrical stimulation (FES) system for the first time. …”
  4. 4

    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…By incorporating the Collatz process and carefully considering key-controlled variables, the proposed model aims to offer enhanced security properties while meeting the necessary criteria for a reliable and effective hashing mechanism. The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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    Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

    Published 1999
    “…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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  8. 8

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

    Published 2020
    “…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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    article
  9. 9

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

    Published 2020
    “…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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    article
  10. 10

    Spherical cavity-expansion forcing function in PRONTO 3D for application to penetration problems by Tabbara, Mazen R.

    Published 2017
    “…In this spirit, a forcing function which is derived from a spherical-cavity expansion analysis has been implemented in PRONTO 3D. …”
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    Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm by El-Kassar, A. N.

    Published 2005
    “…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Pollard's rho algorithm that works in the domain of natural integers. …”
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  13. 13

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

    Published 2024
    “…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. …”
  14. 14

    Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

    Published 2024
    “…<p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. …”
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    Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

    Published 1999
    “…The power system operating at various conditions is treated as a finite set of plants. The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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  16. 16

    A fuzzy basis function network for generator excitation control by Abido, M.A.

    Published 1997
    “…A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. …”
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  17. 17

    Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population by Amr M. Fahmi (21632909)

    Published 2024
    “…To compare the accuracy of a clinical warfarin dosing (CWD) versus genetic warfarin dosing algorithms (GWD) during warfarin initiation. …”
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    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. …”
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  19. 19

    A Comparative Study of Elgamal Based Cryptographic Algorithms by Haraty, Ramzi A.

    Published 2004
    “…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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  20. 20

    A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

    Published 2020
    “…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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