Showing 81 - 100 results of 349 for search '(( algorithm where function ) OR ((( algorithm cost function ) OR ( algorithm a function ))))', query time: 0.14s Refine Results
  1. 81

    Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation by Abualigah, Laith

    Published 2023
    “…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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  2. 82

    A systolic algorithm for VLSI design of a 1/N rate Viterbi decoder by Sait, Sadiq M.

    Published 1989
    “…The systolic algorithm is modeled in AHPL to verify functional correctness. …”
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    article
  3. 83

    Improving the Secure Socket Layer Protocol by modifying its Authentication function by El-Kassar, A. N.

    Published 2017
    “…SSL uses three interdependent cryptographic functions to perform a secure connection. The first function is authentication. …”
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  4. 84

    A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani (14590504)

    Published 2021
    “…In this paper, a multiswarm-intelligence-based algorithm (MSIA) is developed to cope with bound constrained functions. …”
  5. 85

    A parallel tabu search algorithm for VLSI standard-cell placement by Suit, S.M.

    Published 2000
    “…In this work, tabu search placement algorithm is parallelized on a network of workstations using PVM. …”
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    article
  6. 86

    A comparative study of ElGamal based digital signature algorithms by Haraty, Ramzi A.

    Published 2006
    “…We implement the classical and modified ElGamal digital signature scheme 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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  7. 87

    Computational evluation of protein energy functions by Mansour, Nashat

    Published 2014
    “…In this project, we carry out a computational evaluation of putative protein energy functions. …”
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  8. 88

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

    Published 2024
    “…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”
  9. 89

    Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

    Published 2023
    “…To overcome these issues, randomization based neural networks such as random vector functional link (RVFL) network have been proposed. RVFL model has several characteristics such as fast training speed, direct links, simple architecture, and universal approximation capability, that make it a viable randomized neural network. …”
  10. 90

    GAP - A GENETIC ALGORITHM APPROACH TO OPTIMIZE 2-BIT DECODER PLAS by Benten, M. S.

    Published 2020
    “…This paper describes a minimization procedure that uses a genetic algorithm approach to reduce the size to the two bit decoder PLAs. …”
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    article
  11. 91

    A new tabu search algorithm for the long-term hydro scheduling problem by Mantawy, A.H.

    Published 2002
    “…The proposed implementation contributes to the enhancement of speed and convergence of the original tabu search algorithm (TSA). A significant reduction in the objective function over previous classical optimization methods and a simulated annealing algorithm has been achieved. …”
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  12. 92
  13. 93

    BUC algorithm for iceberg cubes by Nasr, George E.

    Published 2003
    “…In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. …”
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  14. 94

    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. …”
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  15. 95

    Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

    Published 2020
    “…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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    masterThesis
  16. 96

    Thyristor controlled phase shifter based stabilizer design usingsimulated annealing algorithm by Abido, M.A.

    Published 1999
    “…This paper presents a thyristor controlled phase shifter (TCPS) based stabilizer design using the simulated annealing (SA) algorithm. …”
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  17. 97

    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. …”
  18. 98

    GATS: A Novel Hybrid Algorithm for Multiobjective Cell Placement in VLSI Circuit Design by Sait, Sadiq M.

    Published 2020
    “…This paper addresses the optimization of cell placement step in VLSI circuit design [1]. A novel hybrid algorithm is proposed for performance and low power driven VLSI standard cell placement. …”
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    article
  19. 99
  20. 100

    Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

    Published 2003
    “…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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