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  1. 2381

    Startup Drift Compensation of MEMS INS Based on PSO–GRNN Network by Songlai Han, Jingyi Xie, Jing Dong

    Published 2025-04-01
    “…The information transmission function between particle swarms was used to find the best spread parameter by iterative optimization, the particle’s position was mapped to the GRNN model, and the GRNN model was constructed with the optimal position of the swarm as the spread parameter. …”
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    Article
  2. 2382

    Research on axial compensation precision puncture control method of prostate puncture robot by Li Bing, Zhu Junwu, Yuan Lipeng

    Published 2025-03-01
    “…Then, an improved adaptive particle swarm optimization (PSO) algorithm based on Levy Flight is proposed to identify parameters of this control model for puncture prostate in this article. …”
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    Article
  3. 2383

    Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage by Tingli Cheng, Minyou Chen, Yingxiang Wang, Bo Li, Muhammad Arshad Shehzad Hassan, Tao Chen, Ruilin Xu

    Published 2018-01-01
    “…Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization (PSO-TLBO), is employed to seek an optimal Pareto front of the proposed dispatch model. …”
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    Article
  4. 2384

    Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet by Ali M. Jasim, Basil H. Jasim, Bilal Naji Alhasnawi, Aymen Flah, Habib Kraiem

    Published 2023-01-01
    “…This work provides a hybrid maximum power tracker strategy to modify the responses of standard maximum power point techniques based on particle swarm optimization-trained adaptive neuro-fuzzy inference system (ANFIS-PSO) to achieve quick and maximum solar power with minimal oscillation tracking. …”
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    Article
  5. 2385

    Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems by Tao Wang, Jun Liu, Lianglun Cheng, Hong Xiao

    Published 2017-09-01
    “…Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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    Article
  6. 2386

    Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM by Hongqiao Huang, Wen Ye, Li Liu, Wenjing Wang, Yan Wang, Huiliang Cao

    Published 2025-04-01
    “…This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. …”
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    Article
  7. 2387

    Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System by Gopisetti Manikanta, Ashish Mani, Hemender Pal Singh, Devendra Kumar Chaturvedi

    Published 2024-02-01
    “…In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. …”
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    Article
  8. 2388

    Techno economic analysis of PV pumping system for rural village in East Java by Aripriharta, Dila Amelia Putri, Aji Prasetya Wibawa, Sujito, Muhammad Cahyo Bagaskoro, Saodah Omar

    Published 2024-12-01
    “…A comparative analysis with the Particle Swarm Optimization (PSO) algorithm indicated that QHBM excels in optimizing RF and ECO₂, whereas PSO demonstrates marginally superior performance in reducing COE. …”
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    Article
  9. 2389

    Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

    Published 2025-06-01
    “…Secongly, the compressed data was used as the input signal for the D-MKELM. Particle swarm optimization (PSO) algorithm was applied to optimize critical parameters, enabling intelligent fault diagnosis. …”
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    Article
  10. 2390

    Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. by Islam Zada, Esraa Omran, Salman Jan, Hessa Alfraihi, Seetah Alsalamah, Abdullah Alshahrani, Shaukat Hayat, Nguyen Phi

    Published 2025-01-01
    “…In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select the features and Extreme Learning Machine and Bootstrap Aggregation (ELM-BA) to classify the features is introduced. …”
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    Article
  11. 2391

    Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department by Ning Dai, Lunjun Li, Kaixin Xu, Zhehao Lu, Xudong Hu, Yanhong Yuan

    Published 2025-01-01
    “…This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. …”
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    Article
  12. 2392

    Estimation of Elasticity of Porous Rock Based on Mineral Composition and Microstructure by Zaobao Liu, Jianfu Shao, Weiya Xu, Chong Shi

    Published 2013-01-01
    “…Then the support vector machine (SVM) optimized by the particle swarm optimization algorithm (PSO) is examined to generate estimations of the ECS based on the mineral composition and microstructures. …”
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    Article
  13. 2393

    Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures by S. Nandhini, A. Rajeswari, N. R. Shanker

    Published 2024-12-01
    “…Abstract In this paper, cyber-attacks in IOT-WSN are detected through proposed optimized-Neural Network algorithms such as (i) Equilibrium Optimizer Neural Network (EO-NN), (ii) Particle Swarm Optimization (PSO-NN), (iii) Single Candidate Optimizer Neural Network (SCO-NN) and (iv) Single Candidate Optimizer Long Short-Term Memory (SCO-LSTM) with different connecting, hidden neural network layers and threat intelligence data. …”
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    Article
  14. 2394

    Development of High Accuracy Classifier for the Speaker Recognition System by Raghad Tariq Al-Hassani, Dogu Cagdas Atilla, Çağatay Aydin

    Published 2021-01-01
    “…In order to enhance noise immunity, we proposed a single hidden layer feed-forward neural network (FFNN) tuned by an optimized particle swarm optimization (OPSO) algorithm. …”
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    Article
  15. 2395

    A Dynamic Processing System for Sensor Data in IoT by Minbo Li, Yanling Liu, Yuanfeng Cai

    Published 2015-08-01
    “…This paper proposes a dynamic sensor data processing (SDP) system to capture and process sensor data continuously on the basis of data streaming technology. Particle Swarm Optimization (PSO) algorithm is employed to train threshold dynamically for data compression avoiding redundancy. …”
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    Article
  16. 2396

    A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions by Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

    Published 2025-06-01
    “…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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    Article
  17. 2397

    A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty by Guilian Wu, Guilian Wu, Jia Lin, Jinlin Liao

    Published 2025-07-01
    “…Third, an improved multi-objective particle swarm optimization (MOPSO) algorithm with adaptive inertia weights accelerates the convergence by 25%. …”
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    Article
  18. 2398

    Evaluation of a robust PID dead-time compensation controller based on the evolutionary computation method by Arun Ramaveerapathiran, R. Muniraj, T. Jarin, S.R. Boselin Prabhu, M. Willjuice Iruthayarajan

    Published 2025-10-01
    “…Tuning is performed by resolving an optimization issue in addition to constraints on robustness using efficient Heterogeneous Comprehensive Learning Particle Swarm Optimization (HCLPSO) evolutionary computation algorithm. …”
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    Article
  19. 2399

    Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method by Bo Chen, Xiao Fu, Xuyuan Guo, Chongshi Gu, Chenfei Shao, Xiangnan Qin

    Published 2019-01-01
    “…The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. …”
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    Article
  20. 2400

    Research on Coordinated Control of Dynamic Reactive Power Sources of DC Blocking and Commutation Failure Transient Overvoltage in New Energy Transmission by Shuqin Sun, Zhenghai Yuan, Dezhi Chen, Zaihua Li, Xiaojun Tang, Yunting Song, Guanghao Zhou

    Published 2025-05-01
    “…A multi-objective particle swarm optimization algorithm, incorporating comprehensive trajectory sensitivity and dynamically adaptive inertia weights, is introduced, alongside Pareto front theory, to achieve rapid and balanced optimization among competing objectives. …”
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    Article