Showing 1 - 20 results of 67 for search '(( algorithm fa function ) OR ( algorithm ((heat function) OR (most function)) ))*', query time: 0.12s Refine Results
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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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    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
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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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    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…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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    Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces by Uzair Sajjad (19646296)

    Published 2021
    “…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”
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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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    article
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    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
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    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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    Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

    Published 2023
    “…This paper aims to search for the optimum school building design under three simultaneous conflicting objective functions: (1) the minimization of overheating hours to less than 40 h as required by Building Bulletin BB101 building code by using passive mitigation measures, (2) the minimization of heating energy use to less than 15 kW/m2 ac cording to passive house requirements and thus the reduction of greenhouse gas emissions, and (3) the mini mization of artificial lighting energy use to less than the current lighting energy use by maximization of daylighting usage without exceeding acceptable glare index in classrooms. …”
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  17. 17

    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
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    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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    article
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