Showing 1 - 20 results of 125 for search '(( elements method algorithm ) OR ((( data swarm algorithm ) OR ( data could algorithm ))))', query time: 0.13s Refine Results
  1. 1

    Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

    Published 2024
    “…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …”
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    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
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    Social spider optimization algorithm: survey and new applications by Abualigah, Laith

    Published 2024
    “…This survey also studied the main applications of this algorithm in different fields, including medical, mathematical, artificial intelligence, engineering, and data engineering, and how this algorithm affected, impacted, and supported the different fields. …”
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    Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant by Shahbaz Hussain (9765320)

    Published 2019
    “…Two contemporary metaheuristic techniques, particle swarm optimization (PSO) and genetic algorithm (GA), have were simultaneously implemented for combined economic emission dispatch (CEED) of an independent power plant (IPP) situated in Pakistan for different load demands. …”
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    Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

    Published 2022
    “…Grasshopper optimization algorithm (GOA) is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good convergence ability towards optima. …”
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    Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

    Published 2023
    “…A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”
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    Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

    Published 2025
    “…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”
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    A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

    Published 2025
    “…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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    Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

    Published 2023
    “…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”