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  1. 2561

    A novel approach for predicting the standardised precipitation index considering climatic factors by Mustafa A. Alawsi, Salah L. Zubaidi, Laith B. Al-badranee

    Published 2022-12-01
    “…., tolerance technique), in addition to, artificial neural network (ANN) combined with particle swarm optimisation (PSO)). The data on climatic factors were applied to build and evaluate the SPI 3 model from 1990 to 2020 for the Al-Kut region. …”
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    Article
  2. 2562
  3. 2563

    Monitoring soil salinization in Arid cotton fields using Unmanned Aerial Vehicle hyperspectral imagery by Jinming Zhang, Jianli Ding, Jiao Tan, Jinjie Wang, Zihan Zhang, Zeyuan Wang, Xiangyu Ge

    Published 2025-06-01
    “…To address these issues, this study proposes a method combining unmanned aerial vehicle (UAV) hyperspectral remote sensing data with a particle swarm optimization Gaussian process regression (PSO-GPR) model. …”
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    Article
  4. 2564

    Structural integrity and hybrid ANFIS-PSO modeling of the corrosion rate of ductile irons in different environments by Ukoba K., Akinribide O.J., Adeleke O.

    Published 2024-07-01
    “…The experimental results from this study were used to validate a model generated from hybrid adaptive neuro-fuzzy inferences system-particle swarm optimization (ANFIS-PSO) algorithms. …”
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    Article
  5. 2565

    Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome by Weirong Xue, Bing Xu, Hui Wang, Xiaoxiao Zhu, Jiajia Qin, Guangshuang Zhou, Peilin Yu, Shengli Li, Yingliang Jin

    Published 2025-05-01
    “…Hyperparameters for each model were optimized using the particle swarm optimization (PSO) algorithm on the validation set. …”
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    Article
  6. 2566

    Predicting the Activity Level of the Great Gerbil (Rhombomys opimus) via Machine Learning by Fan Jiang, Peng Peng, Zhenting Xu, Yu Xu, Ding Yang, Shouquan Chai, Shuai Yuan, Limin Hua, Dawei Wang, Xuanye Wen

    Published 2025-05-01
    “…Because traditional assessment methods are difficult to monitor and cannot effectively predict the population growth trend of R. opimus, an R. opimus activity prediction model was constructed using the particle swarm optimization algorithm‐extreme learning machine (PSO‐ELM). …”
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    Article
  7. 2567

    Development and benchmarking of a thermal lumped model for the magnetron injection gun of the MW-power ITER European gyrotron by A. Antonione, R. Bertazzoni, G. Carannante, K. Cindric, M. Ferrari, A. Leggieri, F. Sanchez, G. De Tommasi

    Published 2025-01-01
    “…The model has been re-implemented in C++ for better computational performances and therefore making it particularly suitable to be exploited by data-driven model identification algorithms and real-time control codes. In this paper the model parameters are identified by using a Particle Swarm Optimization algorithm on experimental data and the model validation is finally carried out on a dedicated dataset, aiming at providing a tool to design and to be integrated into the control system of the machine.…”
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    Article
  8. 2568

    An Enhanced Framework for Assessing Pluvial Flooding Risk with Integrated Dynamic Population Vulnerability at Urban Scale by Xinyi Shu, Chenlei Ye, Zongxue Xu, Ruting Liao, Pengyue Song, Silong Zhang

    Published 2025-02-01
    “…This study uses Jinan, a typical foothill plain city in Shandong Province, as a case study to compare the performance of differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO) in calibrating the SWMM. …”
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    Article
  9. 2569

    A Real Time Coordinated Hydro Governor With Dual STATCOM for Low Frequency Oscillation Damping Using Hybrid Mean DE & TVAPSO by Samarjeet Satapathy, Narayan Nahak, Renu Sharma

    Published 2025-01-01
    “…A new multi-objective mean Differential Evolution with time varying accelerated Particle Swarm Optimization algorithm (MeDETVAPSO) has been implemented to tune controller parameters. …”
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    Article
  10. 2570

    Rotor Location During Atrial Fibrillation: A Framework Based on Data Fusion and Information Quality by Miguel A. Becerra, Diego H. Peluffo-Ordoñez, Johana Vela, Cristian Mejía, Juan P. Ugarte, Catalina Tobón

    Published 2025-03-01
    “…Finally, the IQ criteria were optimized through a particle swarm optimization algorithm. …”
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    Article
  11. 2571
  12. 2572

    A Reputation Value-Based Task-Sharing Strategy in Opportunistic Complex Social Networks by Jia Wu, Fangfang Gou, Wangping Xiong, Xian Zhou

    Published 2021-01-01
    “…The two submodels apply an improved particle swarm algorithm and a Lagrange multiplier, respectively. …”
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    Article
  13. 2573

    Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

    Published 2025-01-01
    “…The proposed methodology combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) for hybrid feature selection, ensuring the selection of the most relevant features for detecting FDIAs. …”
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    Article
  14. 2574

    A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

    Published 2025-06-01
    “… This study aims to evaluate and compare five algorithms in diabetes detection, namely Flower Pollination Neural Network (FPNN), Particle Swarm Optimization Neural Network (PSONN), Bat Artificial Neural Network (BANN), Stochastic Gradient Descent (SGD), and Quadratic Interpolation Flower Pollination Neural Network (QIFPNN). …”
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    Article
  15. 2575

    A Machine Learning Approach to Analyze Manpower Sleep Disorder by Reza Amiri

    Published 2024-01-01
    “…Moreover, a combination of machine learning and metaheuristic algorithms such as eXtreme Gradient Boosting and particle swarm optimization are used to make an accurate predictive model. …”
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    Article
  16. 2576

    Techno-economic modeling and analysis of a PV EV charged with battery energy storage system (BESS) on Kalimantan Island by Aripriharta, Satria Adiguna, Arif N. Afandi, Muhammad Cahyo Bagaskoro

    Published 2025-04-01
    “…This research analyses the optimal combination of solar panels and battery capacity in 11 cities in Kalimantan using particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms to maximize energy output, reduce levelised energy costs, and maximally reduce carbon emissions. …”
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    Article
  17. 2577

    A novel Hadamard matrix based hybrid compressive sensing technique for enhancing energy efficiency and network longevity by Balamurali S, Kathirvelu M, SatheeshKumar Palanisamy, Tagrid Abdullah N. Alshalali

    Published 2025-02-01
    “…By adopting improved versions of Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and novel Hadamard matrix-based hybrid compressed sensing techniques, NHM-HCS enhances the network’s lifespan and improves other performance metrics. …”
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    Article
  18. 2578

    Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

    Published 2025-12-01
    “…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
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    Article
  19. 2579

    Neuro-modelling and fuzzy logic control of a two-wheeled wheelchair system by NIzaruddin M Nasir, Nor Maniha Abdul Ghani, Ahmad Nor Kasruddin Nasir, Mohd Ashraf Ahmad, Mohammad Osman Tokhi

    Published 2025-03-01
    “…Ensuring stable and responsive control, design of optimized PD-type and PID-type fuzzy logic controllers using Particle Swarm Optimization (PSO) were established and were tested under a simulation environment. …”
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    Article
  20. 2580