Showing 1 - 20 results of 65 for search '(( algorithms ((cortex function) OR (most function)) ) OR ( algorithm fa function ))', query time: 0.11s Refine Results
  1. 1

    Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

    Published 2007
    “…A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. …”
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    article
  2. 2

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

    Published 2023
    “…<p>The non-linear property of Chaos is a promising approach to information security, and many accomplishments have been made by combining Chaos with several sub-security domains, including chaos-based stream ciphers, block ciphers, image encryption, and hash functions. Most Chaos-based hash functions are insecure or inefficient due to their dependence on complex, attacked multi-dimensional maps or uncertain, weak one-dimensional maps like logistic and tent. …”
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    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
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    Salp swarm algorithm: survey, analysis, and new applications by Abualigah, Laith

    Published 2024
    “…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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    Radial basis function networks for contingency analysis of bulkpower systems by Refaee, J.A.

    Published 1999
    “…Radial basis function networks (RBFNs) are used for contingency evaluation of bulk power system. …”
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  7. 7

    Belief selection in point-based planning algorithms for POMDPs by Azar, Danielle

    Published 2017
    “…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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    conferenceObject
  8. 8

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

    Published 2017
    “…It is used to allow the client to identify the server and optionally allow the server to identify the client. The most common cryptographic algorithm used for this function is RSA. …”
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    Properties of simulated annealing and genetic algorithms for mapping data to multicomputers by Mansour, Nashat

    Published 1997
    “…We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. …”
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    article
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    Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

    Published 2020
    “…The termevolutionary algorithmis used to refer to any probabilistic algorithmwhose design is inspired by evolutionary mechanisms found in biological species. Most widely known algorithms of this category are genetic algorithms (GA). …”
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    article
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    A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani (14590504)

    Published 2021
    “…Thirty bound constrained benchmark functions are used to evaluate the performance of the proposed algorithm. …”
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    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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    A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks by Saad, Walid

    Published 2012
    “…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …”
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    article
  17. 17

    Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

    Published 2005
    “…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
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  18. 18

    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. …”
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    Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

    Published 2023
    “…An optimization problem is formulated with data rate and BER in the cost function while maintaining energy and power constraints. …”
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    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems by Agushaka, Jeffrey O.

    Published 2022
    “…The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.…”
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