Showing 1 - 20 results of 128 for search '(( algorithm ((goa function) OR (most function)) ) OR ( algorithm cost function ))*', query time: 0.12s Refine Results
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    Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

    Published 2022
    “…Nevertheless, the GOA is unsuitable for addressing multimodal, hybrid functions, and data mining problems. …”
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    A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation by Iman M. Hosseini Naveh (16891482)

    Published 2021
    “…The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). …”
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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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    Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

    Published 2023
    “…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. The optimization is applied to a formulated cost function that considers uncertainty, false alarms, and existing clutters. …”
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    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    Published 2024
    “…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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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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    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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    ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

    Published 2022
    “…The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). …”
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    A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

    Published 2021
    “…Three objective functions are considered to minimize costs, noise pollutions, and the harassment caused by the establishment of a hub for people, a new objective that locates hubs in less populated areas. …”
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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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    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…The goal is to select a set of sensors based on norms of weighted distances cost function. The norms are the Euclidean distance and the Mahalanobis distance between the drone location and the sensors. …”
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