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  1. 2461

    Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

    Published 2025-01-01
    “…To improve the prediction accuracy, this paper proposes a short-term power load-forecasting model of a regional power grid based on multi-source parameter coupling with a long short-term memory neural network (LSTM) and adopts an improved particle swarm optimization (IPSO) algorithm to optimize the LSTM network. …”
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    Article
  2. 2462

    Double-layer energy transaction strategy of multi-microgrids and distribution network with leased shared energy storage by WANG Hui, WU Zuohui, LI Xin, ZOU Zhichao, ZHOU Kerui

    Published 2025-06-01
    “…Finally, an improved particle swarm optimization algorithm combined with the alternating direction multiplier method is adopted to solve the hybrid game model. …”
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    Article
  3. 2463

    Computerised analysis of non-conjugate spiral bevel gear mesh using an advanced and fast-converging tooth contact model by Maksat Temirkhan, Andas Amrin

    Published 2025-07-01
    “…However, most of these methods rely on a discretized approach, resulting in approximate solutions and the use of additional optimization algorithms, such as particle swarm optimization to find the initial contact or grid representation of the tooth surface composed of nodal points. …”
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    Article
  4. 2464

    A method for urban high-voltage distribution network partitioning and energy storage planning by LIU Zhengmao, ZHU Sicheng, HUANG Zhongliang, JIANG Jianjie, ZHU Yitao, ZHANG Youbing, PAN Hongwu

    Published 2025-04-01
    “…A multi-objective particle swarm optimization (MOPSO) is employed to obtain the Pareto frontier, and the rank sum ratio (RSR) is used to determine the optimal site and capacity of energy storage for each partition. …”
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    Article
  5. 2465

    Coordinated Planning of Medium-Voltage and Low-Voltage Flexible Interconnection for Distribution Networks with High Proportion of Distributed Generation by Hanmei PENG, Tang YIN, Qianhao XIAO, Mao TAN, Yongxin SU, Hui LI

    Published 2024-08-01
    “…A hybrid algorithm based on adaptive particle swarm optimization and second-order cone programming is adopted for solution. …”
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    Article
  6. 2466

    Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

    Published 2024-12-01
    “…Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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    Article
  7. 2467
  8. 2468

    Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

    Published 2024-11-01
    “…Then, autoregressive integrated moving average model (ARIMA), extreme learning machine (ELM), support vector regression (SVR), wavelet neural network (Wavelet), recurrent neural network (RNN) and long short-term memory (LSTM) were used to predict COVID-19 epidemic data in Guangdong Province, China; And the prediction performance of each model was compared through prediction accuracy indicators. Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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    Article
  9. 2469

    Probabilistic back analysis method for determining surrounding rock parameters of deep hard rock tunnel by WU Zhong-guang, WU Shun-chuan

    Published 2019-01-01
    “…Second, a multi-output support vector machine (MSVM) was optimized by particle swarm optimization (PSO) algorithm, and an intelligent response surface model was established to reflect the nonlinear mapping relationship between back-analyzed parameters and field monitoring data. …”
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    Article
  10. 2470

    A Mixed Integer Formulation and an NSGA-II for the Cumulative Capacitated Vehicle Routing Problem With Priority Indexes by Karina Corona-Gutierrez, Samuel Nucamendi-Guillen, Iris Martinez-Salazar, J. Marcos Moreno-Vega

    Published 2025-01-01
    “…Likewise, a comparative analysis was conducted between the proposed approaches and a Particle Swarm Optimization algorithm already presented in the literature. …”
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    Article
  11. 2471

    Research on power data security full-link monitoring technology based on alternative evolutionary graph neural architecture search and multimodal data fusion by Zhenwan Zou, Bin Wang, Tao Chen, Jia Chen

    Published 2025-06-01
    “…To solve this problem, this paper proposes a hybrid method that combines multimodal data-aware attacks with Light Gradient Boosting Machine (LightGBM) and Support Vector Regression (SVR) agent models. By using Particle Swarm Optimization-Genetic Algorithm (PSO-GA) for optimal architecture search and combining the dynamic adaptability of Deep Q-Network (DQN) algorithm, this method can automatically identify the most suitable GNN architecture for power data monitoring, thereby improving the adaptive detection and defense efficiency of the system. …”
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    Article
  12. 2472

    Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

    Published 2025-06-01
    “…Furthermore, to improve the detection of gradual faults, artificial intelligence-based fault detection methods were also explored. Specifically, the particle swarm optimization (PSO) algorithm was employed to optimize the hyperparameters of a long short-term memory (LSTM) neural network, leading to the development of a PSO-LSTM fault detection model. …”
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    Article
  13. 2473

    Machine Learning Prediction of Mechanical Properties for Marine Coral Sand–Clay Mixtures Based on Triaxial Shear Testing by Bowen Yang, Kaiwei Xu, Zejin Wang, Haodong Sun, Peng Cui, Zhiming Chao

    Published 2025-07-01
    “…Utilizing this dataset, several predictive models were developed, including a standard Support Vector Machine (SVM), an SVM optimized via Genetic Algorithm (GA-SVM), an SVM enhanced by Particle Swarm Optimization (PSO-SVM), and a hybrid model incorporating Logical Development Algorithm preprocessing a SVM model (LDA-SVM). …”
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    Article
  14. 2474

    Classification and Recognition of Soybean Quality Based on Hyperspectral Imaging and Random Forest Methods by Man Chen, Zhichang Chang, Chengqian Jin, Gong Cheng, Shiguo Wang, Youliang Ni

    Published 2025-03-01
    “…The model parameters were optimized using particle swarm optimization (PSO) and differential evolution (DE) algorithms to improve performance. …”
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    Article
  15. 2475

    Prediction of COD Degradation in Fenton Oxidation Treatment of Kitchen Anaerobic Wastewater Based on IPSO-BP Neural Network by Tianpeng Zhang, Pengfei Ji, Dayong Tian, Rui Xu

    Published 2025-01-01
    “…The Fenton oxidation process is used to treat kitchen anaerobic wastewater, and the effects of H2O2 dosage, Fe2+ dosage, reaction time and pH value on chemical oxygen demand (COD) degradation efficiency are explored. The improved particle swarm optimization (IPSO) algorithm is used to optimize the back propagation (BP) neural network, and a prediction model of COD degradation is established based on IPSO-BP neural network. …”
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    Article
  16. 2476

    Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

    Published 2025-07-01
    “…The aim of this study was to compare the performance of three adaptive neuro-fuzzy inference systems (ANFIS) classification methodologies in classifying mastitis in Holstein dairy cattle: gradient descent (GD)-based ANFIS (GD-ANIFIS), particle swarm optimization (PSO)-based ANFIS (PSO-ANFIS) and genetic algorithm (GA)-based ANFIS (GA-ANFIS). …”
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    Article
  17. 2477

    Height of Hydraulic Fracture Zone Based on PSO_LSSVM Model by Hebin Zhang, Tingting Wang, Bin Wu, Haijun Feng

    Published 2025-06-01
    “…At the same time, this study develops a particle swarm optimization algorithm based on adaptive inertia weight and a least squares support vector machine model to achieve height prediction of water conducting fracture zones. …”
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    Article
  18. 2478

    A Robust Control Strategy for Distributed Generations in Islanded Microgrids by esmaeel rokrok, fariba shavakhi zavareh, jafar soltani, mahmoud reza shakarami

    Published 2020-06-01
    “…All the parameters of controllers are derived via particle swarm optimization (PSO) algorithm in order to minimize an appropriate cost function. …”
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    Article
  19. 2479

    A Coordinated Pumped Storage Dual Compensated Hydro Governor with PSS Action to Damp Electromechanical Power Oscillations by Narayan Nahak, Samarjeet Satapathy

    Published 2022-01-01
    “…Again, subject to critical oscillatory unstable conditions, the DCG is coordinated with PSS through a multiobjective function employing a new modified Differential Evolutionary-Particle swarm optimization (MDEPSO) algorithm. Different case studies with sudden and random SPV and wind penetrations being executed with the proposed controller considering a two area four machine and 39 bus multimachine system with pumped storage hydro units to observe system oscillations are considered. …”
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    Article
  20. 2480

    Heat Storage Decoupling Method Based on Coordinated Load Scheduling Model by Yi LEI, Mingzhen LIU, Kaimin LIN

    Published 2019-07-01
    “…The power-heat coupling characteristics of CHP units are firstly studied; and then a heat-power decoupling scheme is formulated for wind power-heat storage compensation, and a multi-objective load-dispatching model is built with the objective of minimizing both the operation cost and pollutant emission of the power system; finally, the corrected multi-objective particle swarm optimization algorithm is used to solve the model, and the diversity of the Pareto set is maintained by using niche method. …”
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    Article