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  1. 2341

    Elastic Momentum-Enhanced Adaptive Hybrid Method for Short-Term Load Forecasting by Wenting Zhao, Haoran Xu, Peng Chen, Juan Zhang, Jing Li, Tingting Cai

    Published 2025-06-01
    “…This paper proposes a hybrid approach combining traditional time series models (ARIMA) with machine learning models (SVR). The particle swarm optimization (PSO) algorithm is improved by adjusting its elastic momentum, and the enhanced APSO algorithm is employed to optimize the adaptive weights of the hybrid model. …”
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    Article
  2. 2342

    Calculation Methods for the Permeability Coefficient of Concrete Face Rockfill Dam with Cracks by Zhongwen Shi, Zhongru Wu, Chongshi Gu, Bo Chen, Hailong Zhang, Wenzhong Yin, Bangbin Wu

    Published 2019-01-01
    “…Moreover, an inversion algorithm based on particle swarm optimization and support vector machine was proposed and applied. …”
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    Article
  3. 2343

    The Spacecraft Parabolic Antenna Payload Orientation Estimation Method Based on the Step Effect of Measured Radar Cross Section Sequences by Junzhi Li, Xin Ning

    Published 2024-11-01
    “…This method employs an optimized model and particle swarm optimization to achieve the pointing estimation of the parabolic antenna payload. …”
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    Article
  4. 2344

    A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

    Published 2024-10-01
    “…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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    Article
  5. 2345

    Research on Deformation Prediction of Foundation Pit Based on PSO-GM-BP Model by Dongge Cui, Chuanqu Zhu, Qingfeng Li, Qiyun Huang, Qi Luo

    Published 2021-01-01
    “…The results show that both the GM (1, 1) and BP neural network models can predict accurate results. The prediction optimized by the particle swarm algorithm is more accurate and has more substantial applicability. …”
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    Article
  6. 2346

    Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

    Published 2025-08-01
    “…Subsequently, particle swarm optimization (PSO) was utilized to adaptively determine the MCKD parameters, and the AMCKD algorithm was applied to enhance the features of the filtered signal. …”
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    Article
  7. 2347

    Research on Dynamic Dissolving Model and Experiment for Rock Salt under Different Flow Conditions by Xinrong Liu, Xin Yang, Zuliang Zhong, Ninghui Liang, Junbao Wang, Ming Huang

    Published 2015-01-01
    “…The artificial intelligence algorithm, Particle Swarm Optimization algorithm (PSO), was finally introduced to conduct inverse analysis of parameters on the established model, whose calculation results coincide with the experimental data.…”
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    Article
  8. 2348

    Multiagent, multitimescale aggregated regulation method for demand response considering spatial–temporal complementarity of user-side resources by Tingzhe Pan, Chao Li, Chen Yang, Zijie Meng, Zongyi Wang, Zean Zhu

    Published 2025-04-01
    “…For the day-ahead timescale, we developed an improved particle swarm optimization (IPSO) algorithm that dynamically adjusts the number of particles based on intraday outcomes to optimize the regulation strategies. …”
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    Article
  9. 2349

    Maximum Power Exploitation of Photovoltaic System under Fast-Varying Solar Irradiation and Local Shading by Yi-Jui Chiu, Bi Li, Chin-Ling Chen, Shui-Yang Lien, Ding Chen, Ji-Ming Yi, Yung-Hui Shih

    Published 2022-01-01
    “…In addition, under fast-varying solar irradiation and local shading, the speed, ability, and stability of the improved MPPT system with the PF-MPPT algorithm when tracking the maximum power were 9.52, 1.32, and 1.84 times of the MPPT system with the P&O algorithm and 2.18, 1.41, and 2.00 times of the MPPT system with the particle swarm optimization algorithm, respectively.…”
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    Article
  10. 2350

    PuTMO3 systems crystal structures prediction and stability analysis based on first principles by Zexin Jiang, Jintao Wang, Yilin Fang, Tao Wang, Rui Zhou, Wenli Yu, Rusong Li, Ning Gao

    Published 2025-05-01
    “…Abstract Based on particle swarm optimization algorithm and first-principle calculations, the most stable structures of 10 different PuTMO3 systems are predicted according to their thermodynamical, mechanical and dynamical properties. …”
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    Article
  11. 2351

    Prediction of Chemical Corrosion Rate and Remaining Life of Buried Oil and Gas Pipelines in Changqing Gas Field by Xianbing Li, Rui Liu, Dong Ma, Yang Bai, Yukai Shi, Badm Anhouck

    Published 2023-01-01
    “…By improving the inertial weights and learning factors of the traditional particle swarm algorithm, the parameters of the generalized regression neural network are optimized and selected, and the corrosion rate prediction model of buried pipelines is finally constructed. …”
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    Article
  12. 2352

    A strategic approach to the placement of PV-integrated EV charging stations for enhancing the distribution network performance by Raj Chakraborty, Subhojit Dawn, Priyanath Das, Diptanu Das, Sadhan Gope, Md. Minarul Islam, Taha Selim Ustun

    Published 2025-09-01
    “…The outcomes have been compared with Grey Wolf Optimizer, particle swarm optimization (PSO), and whale optimization algorithm (WOA) to validate the effectiveness of the optimal planning to allocate the EVCS and PV units. …”
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    Article
  13. 2353

    Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

    Published 2025-07-01
    “…Particle Swarm Optimization (PSO) optimizes neural network weight assignments, dynamically fine-tuning network topologies depending on the complex student dataset. …”
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    Article
  14. 2354

    Research on temperature and humidity compensation method of vehicle gas sensor based on SCA-PSO support vector regression by Lv Yingming, Yuan Wenping

    Published 2025-05-01
    “…In this paper, a vehicle-mounted vehicle exhaust gas detection device is designed and a sensor temperature and humidity compensation method based on Support Vector Regression (SVR), Sine Cosine Algorithm(SCA) and Particle Swarm Optimization (PSO) is proposed. …”
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    Article
  15. 2355

    A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring by Can WANG, Jianxin PENG, Xiaowen ZHANG

    Published 2020-02-01
    “…The mean recognition rate for simple snoring sounds and snoring sounds related to respiratory disorder events is more than 91.14% by using the grid search, a genetic algorithm and particle swarm optimization methods. …”
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    Article
  16. 2356

    Control Method of Microgrid Grid Connected Inverter Based on Quantum GA-PID by Yunqing Qu

    Published 2025-07-01
    “…Therefore, a proportional integral derivative control method of the quantum genetic algorithm and particle swarm optimization has been proposed, which can achieve stable and efficient operation of microgrids.The total harmonic distortion of the improved controller was 1.03%, which was 1.98% lower than the traditional method and far below the national standard of 5%; The prediction accuracy wad on average 82%, 51%, and 54% higher than the other three classic algorithms; After the improvement of sag, the smoothness of microgrid switching had been increased, avoiding severe shaking. …”
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    Article
  17. 2357

    Fault Diagnosis of Train Bogie Bearing Based on Multi-scale Sample Entropy Improved Extreme Learning Machine by JIN Zhenzhen, HE Deqiang, MIAO Jian, XU Weichang

    Published 2021-01-01
    “…Then, the extreme learning machine is optimized by particle swarm optimization, and the input weights and hidden node thresholds are obtained. …”
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    Article
  18. 2358

    Coverage Restoration Method for Wireless Sensor Networks of Distributed PV System by Zhixin Fu, Zhen Liu, Yue Yuan, Min Zhao, Qiaomu Li

    Published 2015-02-01
    “…According to the performance degradation problem caused by nodes failure in PV monitoring network, particle swarm optimization (PSO) of natural selection based on random weight is proposed in this paper to optimize monitoring performance. …”
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    Article
  19. 2359

    A Key Management Method Based on Dynamic Clustering for Sensor Networks by Ying Zhang, Bingxin Zheng, Pengfei Ji, Jinde Cao

    Published 2015-07-01
    “…Considering the nodes’ capture probability, particle swarm optimization algorithm was used to optimize the clustering of sensor networks. …”
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    Article
  20. 2360

    Fractional-order backstepping sliding mode control for the speed tension and screw down system of the reversible cold strip rolling mill by Yujing Guo, Zhuang Ma, Minghao Lin

    Published 2024-12-01
    “…Based on the finite time observer, a fractional-order backstepping sliding mode controller is designed for each sub-system of the speed tension and screw down system of RCSRM. The Particle Swarm Optimization (PSO) algorithm is used to optimize the main parameters of the designed controller. …”
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    Article