Showing 1 - 16 results of 16 for search '(( binary 1 based optimization algorithm ) OR ( less based from optimization algorithm ))', query time: 0.13s Refine Results
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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
    “…In this paper, a recent swarm intelligence metaheuristic method called RSO which is inspired by the social and hunting behavior of a group of rats is enhanced and explored for FS problems. 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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    Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

    Published 2022
    “…Metaheuristic algorithms have also been presented in four primary behavior-based categories, i.e., evolutionary-based, swarm-intelligence-based, physics-based, and human-based, even though some literature works presented more categorization. …”
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    Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by D., Sathish Kumar

    Published 2023
    “…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems.…”
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    Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by M. Premkumar (12757280)

    Published 2023
    “…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems. …”
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    Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik, Rafikiran

    Published 2023
    “…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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    Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik Rafikiran (15838929)

    Published 2023
    “…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AASP&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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    Optimisation of PV Cleaning Practices: Comparison Between Performance Based and Periodic Based Approaches by ALHAJERI, RASHED ABDULLA

    Published 2018
    “…Optimized periodic based manual cleaning approach where panels are cleaned on a fixed period taken as the rounded average from the performance based manual cleaning approach. 4. …”
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    A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions by Chakarajamula Hussaian Basha (21633167)

    Published 2024
    “…<p dir="ltr">At present, fossil fuel-based power generation systems are reducing drastically because of their less availability in nature. …”
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    A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

    Published 2023
    “…The important feature subset is identified using the modified Binary Grey Wolf Optimization Particle Swarm Optimization (BGWOPSO) algorithm. …”
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    A method for data path synthesis using neural networks by Harmanani, H.

    Published 2017
    “…The proposed algorithm has a running time complexity of O(1) for a neural network with n vertices and c cliques. …”
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