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  1. 201

    Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

    Published 2025-05-01
    “…Aiming at the problem that the current residual effective life prediction (RUL) technique for proton exchange membrane fuel cells (PEMFCs) has poor prediction effect in the medium and long term, a residual life prediction method based on the Improved Gray Wolf Optimization algorithm (IGWO) and Echo State Network (ESN) is proposed, in which the voltage of the electric stack is firstly selected as a health indicator, and the PEMFC dataset is processed by using convolutional smoothing filtering method to carry out data Smoothing and normalization are used to effectively reduce the interference of outliers on the subsequent model training. …”
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  2. 202

    Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access by Xiping Ma, Xiping Ma, Xiaoyang Dong, Haitao Xiao, Yaxin Li, Rui Xu, Kai Wei, Juanjuan Cai, Juan Wei

    Published 2025-01-01
    “…Both layers are solved using the Improved Whale Optimization algorithm (IWOA). Then, the IEEE-33 node distribution system was taken as a simulation example to verify the effectiveness and superiority of the proposed model and algorithm.…”
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  3. 203

    Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

    Published 2025-04-01
    “…For the prediction of VIV parameters, the Random Forest model is the most effective. The RMSE values of the improved optimal algorithm are 0.017, 0.026, and 0.295, and the R<sup>2</sup> values are 0.9421, 0.8875, and 0.9462. …”
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  4. 204

    Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load by Chao Xing, Jiajie Xiao, Xinze Xi, Jingtao Li, Peiqiang Li, Shipeng Zhang

    Published 2024-09-01
    “…The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. …”
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  5. 205

    Optimization method of time of use electricity price considering losses in distributed photovoltaic access distribution network by Tianshou Li, Qing Xu, Weiwu Li, Xinying Wang, Zhengying Liu

    Published 2025-01-01
    “…And refer to the basic requirements for electricity pricing in the distribution network, set a series of constraints for optimizing electricity prices. Applying an improved imperialist competition algorithm this paper integrates Tent chaotic reverse learning to solve a multi-objective optimization model and obtain an optimized time of use electricity pricing plan. …”
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  6. 206
  7. 207

    Improving the performance of a two-phase ejector using genetic algorithm based on secondary fluid entrainment rate by M. Moghadasi, M. Moraveji, O. Alizadeh

    Published 2022-12-01
    “…Using a multi-objective genetic algorithm, the optimal values for each parameter are obtained. …”
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  8. 208

    An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

    Published 2024-10-01
    “…This protocol initially employs the root mean square (RMS) of distance within the energy consumption model to determine the optimal number of cluster heads. …”
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    Article
  9. 209
  10. 210

    An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date by Pedro Palominos, Mauricio Mazo, Guillermo Fuertes, Miguel Alfaro

    Published 2025-01-01
    “…This study evaluates the efficiency of a swarm intelligence algorithm called marriage in honey-bee optimization (MBO) in solving the single-machine weighted earliness/tardiness problem, a type of NP-hard combinatorial optimization problem. …”
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  11. 211

    Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy by Tingxin Wen, Haoting Meng

    Published 2025-03-01
    “…The self-organizing mapping network method is employed to initialize the EV routing, and an improved adaptive large neighborhood search (IALNS) algorithm is developed to solve the optimization problem. …”
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  12. 212

    Impact of parameter control on the performance of APSO and PSO algorithms for the CSTHTS problem: An improvement in algorithmic structure and results. by Muhammad Ahmad Iqbal, Muhammad Salman Fakhar, Syed Abdul Rahman Kashif, Rehan Naeem, Akhtar Rasool

    Published 2021-01-01
    “…Recently, the authors have published the best-achieved results of the CSTHTS problem having quadratic fuel cost function of thermal generation using an improved variant of the Accelerated PSO (APSO) algorithm, as compared to the other previously implemented algorithms. …”
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  13. 213

    Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

    Published 2025-07-01
    “…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
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  14. 214

    A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling by Guorong Fan, Chao Li, Xinyun Shao, Fangzheng Zhen, Yao Huang

    Published 2025-12-01
    “…To solve large-scale problems, an improved adaptive large neighborhood search algorithm (ALNS) is designed accordingly. …”
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  15. 215

    Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

    Published 2025-12-01
    “…The model's hyperparameters are optimized by the Improved Whale Optimization Algorithm (IWOA), which improves search efficacy by including chaotic mapping, a nonlinear shrinkage factor, and a Levy flight strategy. …”
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  16. 216

    Improving Trajectory Tracking of Differential Wheeled Mobile Robots With Enhanced GWO-Optimized Back-Stepping and FOPID Controllers by Li Qiang, Hooi Hung Tang, Nur Syazreen Ahmad

    Published 2025-01-01
    “…Simulations demonstrate the superior performance of the proposed GWO-SMA algorithm compared to existing optimization techniques, such as Particle Swarm Optimization (PSO), Gazelle Optimization Algorithm (GOA), and its individual components, GWO and SMA, which have shown strong performance in recent literature for optimizing PID-type controllers. …”
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  17. 217
  18. 218

    An improved salp swarm algorithm for permutation flow shop vehicle routing problem by Yanguang Cai, Huajun Chen

    Published 2025-02-01
    “…Aiming at the requirements of collaborative optimization of production scheduling and logistics transportation scheduling, a mathematical model of the problem is established, and an improved salp swarm algorithm is proposed to solve it. …”
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  19. 219

    Improved artificial protozoa optimizer: A new method for solar photovoltaic parameter estimation by Wenhao Lai, Duoduo Liu, Jialong Yang, Lei Guo, Weijin Qian, Jiaojiao Wu, Haifeng Zhou

    Published 2025-09-01
    “…We propose an improved Artificial Protozoa Optimizer (iAPO) algorithm for the parameter estimation of photovoltaic cells. …”
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  20. 220

    Research on Vehicle Route Optimization for Half-Open Multi-Energy Urban Distribution Considering Order Priority by Mingxuan Zhang

    Published 2025-01-01
    “…On the basis of the sparrow search algorithm, Tent chaotic mapping is added and random key coding strategy is inserted for discretization, which increases the diversity of the initial population of the sparrow search algorithm and improves the algorithm&#x2019;s global optimization seeking ability. …”
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