Showing 141 - 160 results of 453 for search 'been swarm algorithm', query time: 0.11s Refine Results
  1. 141

    Systematic Review: Particle Swarm Optimization (PSO) based Load Balancing for Cloud Computing by Darakhshan Syed, Ghulam Muhammad Shaikh, Safdar Rizvi

    Published 2024-06-01
    “…Static, heuristics-based, traditional dynamic and metaheuristic-based algorithms are ways that have been used for effective load balancing. …”
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    Article
  2. 142

    Hybrid Ensemble Pruning Using Coevolution Binary Glowworm Swarm Optimization and Reduce-Error by Xuhui Zhu, Zhiwei Ni, Pingfan Xia, Liping Ni

    Published 2020-01-01
    “…It is hard to look for the exact result via the searching of intelligent algorithms or pruning of diversity measures. On the basis, we propose a hybrid ensemble pruning approach employing coevolution binary glowworm swarm optimization and reduce-error (HEPCBR). …”
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    Article
  3. 143

    Automated Pruning Framework for Large Language Models Using Combinatorial Optimization by Patcharapol Ratsapa, Kundjanasith Thonglek, Chantana Chantrapornchai, Kohei Ichikawa

    Published 2025-05-01
    “…Two techniques were particularly studied, i.e., particle swarm optimization (PSO) and whale optimization algorithm (WOA). …”
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    Article
  4. 144
  5. 145

    Chaotic-mapping and Gaussian perturbation-based multi-channel constant modulus blind equalization by HU Shuang, FENG Jiao, ZHANG Zhizhong, LI Peng, ZHOU Hua

    Published 2025-05-01
    “…The improved constant modulus blind equalization algorithm based on particle swarm optimization is a new blind equalization method that introducing particle swarm optimization to find the optimal solution for the equalizer, thereby improving the convergence speed of the algorithm. …”
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    Article
  6. 146

    Unite and conquer approach for data clustering based on particle swarm optimization and moth flame optimization by E. Mosavi, S.A. Shahzadeh Fazeli, E. Abbasi, F. Kaveh-Yazdy

    Published 2025-06-01
    “…To address this issue, metaheuristic algorithms have been proposed as a type of approximate optimization algorithm capable of identifying almost optimal solutions. …”
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    Article
  7. 147

    Multi-modal prediction of breast cancer using particle swarm optimization with non-dominating sorting by Vijayalakshmi S, John A, Sunder R, Senthilkumar Mohan, Sweta Bhattacharya, Rajesh Kaluri, Guang Feng, Usman Tariq

    Published 2020-11-01
    “…Particle swarm optimization has been identified as one of the most powerful and efficient technique for the diagnosis of breast cancer guiding physicians towards timely and accurate treatment. …”
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    Article
  8. 148

    Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times by N. Micheal Mathavavisakan, K. Indhira, Aliakbar Montazer Haghighi

    Published 2025-08-01
    “…To complement the performance analysis, a cost function was formulated and optimized using advanced techniques, including the grey wolf optimizer (GWO), bat algorithm (BA), whale optimization algorithm (WOA), and cat swarm optimization (CSO). …”
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    Article
  9. 149

    QoS-Based Web Service Discovery in Mobile Ad Hoc Networks Using Swarm Strategies by Filomena de Santis, Delfina Malandrino

    Published 2014-01-01
    “…The protocol has been specifically designed to work in mobile ad hoc network scenarios operating with Beeadhoc, a well-known routing algorithm inspired by nature. …”
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  10. 150

    Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

    Published 2022-01-01
    “…Based on the data preprocessing, global and local interpretations are performed according to the Shapley additive explanations (SHAP) analysis, and the redundant features in the data set are screened to identify the porosity, AC, CAL, and GR slope as the four most important features. The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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    Article
  11. 151

    Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

    Published 2025-01-01
    “…Weighted cognitive avoidance particle swarm optimization for the XGBoost (WCAPSO-XGB) model has been proposed for credit score classification. …”
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    Article
  12. 152

    EPICS: error-preserved and interpolation-corrected surrogate-assisted particle swarm optimization for complex optimization by Tongbang Jiang, Jeng-Shyang Pan, Shu-Chuan Chu, Chaoli Sun, Václav Snášel

    Published 2025-06-01
    “…Abstract Surrogate-assisted particle swarm optimization (SAPSO) has been proven to be efficient in solving high-dimension problems. …”
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    Article
  13. 153

    A two-stage optimization model for relief logistics and distribution to disaster survivors under two-fold uncertainty by Palash Sahoo

    Published 2024-12-01
    “…., expected value, pessimistic value, and optimistic value) is applied to reduce the type-2 zigzag uncertain variable to the type-1 zigzag uncertain variable. The genetic algorithm and particle swarm optimization techniques have been proposed to find the optimal solution for the two deterministic models. …”
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    Article
  14. 154

    Bio-Inspired Metaheuristics in Deep Learning for Brain Tumor Segmentation: A Decade of Advances and Future Directions by Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana, Wahyu Caesarendra, Nurul Huda

    Published 2025-05-01
    “…This review systematically examines developments from 2015 to 2025, focusing on the integration of nature-inspired optimization methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and novel hybrids including CJHBA and BioSwarmNet into deep learning-based brain tumor segmentation frameworks. …”
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  15. 155
  16. 156

    Particle Swarm Optimization-Based Direct Inverse Control for Controlling the Power Level of the Indonesian Multipurpose Reactor by Yoyok Dwi Setyo Pambudi, Wahidin Wahab, Benyamin Kusumoputro

    Published 2016-01-01
    “…A neural network-direct inverse control (NN-DIC) has been simulated to automatically control the power level of nuclear reactors. …”
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    Article
  17. 157

    Entropy-Driven Global Best Selection in Particle Swarm Optimization for Many-Objective Software Package Restructuring by Amarjeet Prajapati, Anshu Parashar, null Sunita, Alok Mishra

    Published 2021-01-01
    “…Many real-world optimization problems usually require a large number of conflicting objectives to be optimized simultaneously to obtain solution. It has been observed that these kinds of many-objective optimization problems (MaOPs) often pose several performance challenges to the traditional multi-objective optimization algorithms. …”
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  18. 158

    A Hybrid P&O-Fuzzy-Based Maximum Power Point Tracking (MPPT) Algorithm for Photovoltaic Systems Under Partial Shading Conditions by Hamed Karimi, Alireza Siadatan, Afshin Rezaei-Zare

    Published 2025-01-01
    “…This paper proposes a new MPPT approach that combines Perturb & Observe (P&O) and Fuzzy Logic Controller (FLC) with the Particle Swarm Optimization (PSO) algorithm. The FLC algorithm is then used to maximize search accuracy. …”
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    Article
  19. 159

    The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020) by Parsa Ghannadi, Seyed Sina Kourehli, Seyedali Mirjalili

    Published 2022-09-01
    “…Among different algorithms, the particle swarm optimization (PSO) approach has been of the most popular ones. …”
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  20. 160

    Research on Optimization Method of Coal Blending for Carbon Emission Reduction Based on Bi-level Programming by CHEN Siqin, ZHU Yinan, LI Xiaochen, WANG Xuehai

    Published 2023-04-01
    “…The lower layer is the goal of the power plant sector, pursuing the minimization of coal blending cost and carbon emission cost. The chaotic particle swarm optimization (CPSO) algorithm was used to solve the model. …”
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