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    CMA-PSO Algorithm for Fuzzy Cloud Resource Scheduling by LI Cheng-yan, SONG Yue, MA Jin-tao

    Published 2022-02-01
    “…Aiming at the multiobjective cloud resource scheduling problem, with the goal of optimizing the total completion time and total execution cost of the task, a fuzzy cloud resource scheduling model is established using the method of fuzzy mathematics.Utilizing the advantage of the covariance matrix that can solve the non-convexity problem, adopting the covariance evolution strategy to initialize the population, a hybrid intelligent optimization algorithm CMA-PSO algorithm (covariance matrix adaptation evolution strategy particle swarm optimization,CMA-PSO) is proposed to solve the fuzzy cloud resource scheduling model.The Cloudsim simulation platform was used to randomly generate cloud computing resource scheduling data, and the CMA-PSO algorithm was tested.The experimental results showed that compared with the PSO algorithm (particle swarm optimization), the optimization capability of CMA-PSO algorithm is increased by 28%, the number of iterations of CMA-PSO algorithm is increased by 20%, and it has good load balancing performance.…”
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    A Hybrid Optimization Approach for Residential Energy Management by Yantai Huang, Jinjiang Zhang, Yujie Mo, Shuijin Lu, Junchao Ma

    Published 2020-01-01
    “…The discrete variables are optimized by using a particle swarm optimization (PSO) algorithm, whilst the continuous variables are determined by using a gradient-based deterministic algorithm. …”
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    An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

    Published 2025-09-01
    “…A comprehensive study compares the HHO technique with established methods such as perturb and observe (P&O), modified P&O (MP&O), incremental conductance (IC), Spline MPPT, particle swarm optimization (PSO), grasshopper optimization (GHO), and grey wolf optimization (GWO) across fast-changing irradiance, partial shading, complex partial shading, and load-changing conditions. …”
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    Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

    Published 2023-08-01
    “…This study applies an artificial neural network (ANN) integrated with the particle swarm optimisation algorithm (PSO-ANN) for simulating monthly WL of the Tigris River in Alkut City, Iraq. …”
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