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  1. 1661

    De-noising algorithms for the raised cosine pulse signal using the minimum-energy frame in the discrete signal space by Ying-hai XIE, Wei YANG, Ting-ting FAN

    Published 2012-03-01
    “…The de-noising algorithms were proposed for the raised cosine pulse signal using minimum-energy(wavelet) frame in the discrete signal space.For the given two minimum-energy frames,the decomposition coefficients of sampled sequence appeared significant statistical characteristics difference between the raised cosine pulse signal and additive Gaussian noise under the frames’sub-sequences.Based on this,two threshold de-noising algorithms were provided to makes full use of the merit that the frame was fit for the de-noising work,they removed partial noise component while keeping the component of original signal and got effic nt de-noising result.The simulation results show that,when the modulating method is BPSK and its raised cosine pulse signal is polluted by the additive Gaussian noise,then if add a pre-processing link to denoise the receiving waveform using the algorithms,the receiver can greatly increase the signal-to-noise ratio of receiving signal and have about 3.1dB and 2.7dB performance gain of bit error ratio,respectively.…”
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  2. 1662

    A cluster based routing for maximizing the lifetime of underwater wireless sensor network using gravitational search algorithm by Shyamsundar R, Harshavarthan M, Shankar Thangavelu

    Published 2025-03-01
    “…The proposed GSA has been compared with competitive meta-heuristic algorithms, including Particle Swarm Optimization, Whale Optimization Algorithm, and Moth Flame Optimizer.…”
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    Article
  3. 1663

    An Effective Reactive Power Compensation Method and a Modern Metaheuristic Algorithm for Loss Reduction in Distribution Power Networks by Thang Trung Nguyen, Kim Hung Le, Tan Minh Phan, Minh Quan Duong

    Published 2021-01-01
    “…In the method, local capacitors at each load are determined to increase power factor of load to an expected value first and then a number of capacitors are placed in distribution lines with two factors, location and capacity by using the three applied methods. Particle swarm optimization (PSO), parasitism predation algorithm (PPA), and tunicate swarm algorithm (TSA) are applied for the proposed method on four distribution systems with 15, 33, 69, and 85 buses. …”
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    Article
  4. 1664

    A Thinning Method of Linear And Planar Array Antennas To Reduce SLL of Radiation Pattern By GWO And ICA Algorithms by H. Rezagholizadeh, D. Gharavian

    Published 2018-12-01
    “…Thinning is performed using Genetic, Particle Swarm, Imperialist Competitive and Grey Wolf algorithms. …”
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    Article
  5. 1665

    Minimum-Fuel Ascent of Hypersonic Vehicle considering Control Constraint Using the Improved Pigeon-Inspired Optimization Algorithm by Jiahao He, Yanbin Liu, Shuanglin Li, Yue Tang

    Published 2020-01-01
    “…The comparison results show that the proposed algorithm outperforms particle swarm optimization (PSO) and standard PIO on trajectory optimization. …”
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    Article
  6. 1666

    A Robust Path Following Algorithm Based on the Orthogonal Bishop Parametrization for A non–Holonomic Mobile Manipulator by Mazur Alicja, Dyba Filip

    Published 2025-06-01
    “…The achieved results are verified with an exemplary simulation study. The proposed algorithm assures asymptotic convergence of errors to zero for less strict requirements imposed on the desired path and in the case of partial knowledge of the dynamics model.…”
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  7. 1667

    Research on COP Prediction Model of Chiller Based on PSO-SVR by Zhou Xuan, Cai Panpan, Lian Sizhen, Yan Junwei

    Published 2015-01-01
    “…Since the difficulty of building mechanism model and the structure of COP model of chiller is complex, greatly affected by operating parameter, a COP prediction model of chiller is proposed based on Support Vector Regression, and the parameters are optimized by Particle Swarm Optimization algorithm. In this paper, 396 sets of operating data of chiller of a shopping mall are randomly selected to train and test this model. …”
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    Article
  8. 1668

    Optimizing Personalized Recommender Systems for Teachers’ Digital Learning Models Using Deep Learning Algorithms by Jun Zhong, Wenjuan Zhang

    Published 2025-01-01
    “…To address this issue, this paper proposes a personalized recommendation algorithm based on Graph Neural Networks (PRAGNN) for teachers’ digital learning models. …”
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    Article
  9. 1669

    Optimizing Kernel Extreme Learning Machine based on a Enhanced Adaptive Whale Optimization Algorithm for classification task. by ZeSheng Lin

    Published 2025-01-01
    “…Furthermore, inspired by the grey wolf optimization algorithm, use 3 excellent particle surround strategies instead of the original random selecting particles. …”
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    Article
  10. 1670

    What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

    Published 2022-06-01
    “…The sample size effect is most evident when the sample size drops below 30%, which is equivalent to six weeks of continuously collected hourly data. Although algorithms react differently to the number of predictors, their performance was typically boosted by adding more predictors, especially the particle count and humidity. …”
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    Article
  11. 1671

    Research on Adaptive Planning of Three-Dimensional Trajectory for Uncrewed Aerial Vehicle Inspection Based on Nonlinear Weibull Algorithm by Zhuang Liu, Ning Yang, Jiaxing Fu, Huanqing Cai, Xuebei Wei

    Published 2025-01-01
    “…The results show that under flight environments with varying complexity of obstacle and threat region distribution, compared with the Particle Swarm Optimization algorithm (PSO), Butterfly Optimization Algorithm (BOA), and Reptile Search Algorithm (RSA), NWFRSA can effectively reduce the path cost (by 4.53%–34.47%), contributing to improved.…”
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    Article
  12. 1672

    A Hybrid Machine Learning Framework for Early Fault Detection in Power Transformers Using PSO and DMO Algorithms by Mohammed Alenezi, Fatih Anayi, Michael Packianather, Mokhtar Shouran

    Published 2025-04-01
    “…This study introduces a novel machine learning framework that integrates Particle Swarm Optimization (PSO) and Dwarf Mongoose Optimization (DMO) algorithms for feature selection and hyperparameter tuning, combined with advanced classifiers such as Decision Trees (DT), Random Forests (RF), and Support Vector Machines (SVM). …”
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    Article
  13. 1673

    Performance of Various Voltage Stability Indices in a Stochastic Multiobjective Optimal Power Flow Using Mayfly Algorithm by Rebeccah Kyomugisha, Christopher Maina Muriithi, George Nyauma Nyakoe

    Published 2022-01-01
    “…Overall, VCPI and Lmn index provided the best and worst average performance in both operating scenarios, respectively. Also, the MOMA algorithm demonstrated superior performance against the multiobjective harris hawks algorithm (MHHO), multiobjective Jaya algorithm (MOJAYA), multiobjective particle swarm algorithm (MOPSO), and nondominated sorting genetic algorithm III (NSGA-III) algorithms. …”
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    Article
  14. 1674

    Research on Unmanned Aerial Vehicle Emergency Support System and Optimization Method Based on Gaussian Global Seagull Algorithm by Songyue Han, Mingyu Wang, Junhong Duan, Jialong Zhang, Dongdong Li

    Published 2024-12-01
    “…Through simulation experiments, the GLSOAG demonstrates significant advantages over the Seagull Optimization Algorithm (SOA), Particle Swarm Optimization (PSO), and Beetle Antennae Search Algorithm (BAS) in terms of convergence speed, optimization accuracy, and stability. …”
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  15. 1675
  16. 1676

    Research on Motion Transfer Method from Human Arm to Bionic Robot Arm Based on PSO-RF Algorithm by Yuanyuan Zheng, Hanqi Zhang, Gang Zheng, Yuanjian Hong, Zhonghua Wei, Peng Sun

    Published 2025-06-01
    “…To address this shortcoming, this study presents a motion transfer method from the human arm to a bionic robot arm based on the hybrid PSO-RF (Particle Swarm Optimization-Random Forest) algorithm to improve joint space mapping accuracy and dynamic compliance. …”
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    Article
  17. 1677

    A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

    Published 2024-11-01
    “…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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    Article
  18. 1678

    Optimized load frequency controller for microgrid with renewables and EVs based recent multi-objective mantis search algorithm by Osama Elbaksawi, Rovan Fathy, Ahmed Ali Daoud, R.A. Abd El-aal

    Published 2025-06-01
    “…The proposed approach reduces these deviations by approximately 43 % to 51 %, 54 % to 67 %, and 73 % to 88 % compared to the particle swarm optimization (PSO), marine predator algorithm (MPA), and genetic algorithm (GA), respectively. …”
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    Article
  19. 1679

    Improved Estimation Procedure of Cage-Induction-Motor-Equivalent Circuit Parameters Based on Two-Stage PSO Algorithm by Jovan Vukašinović, Saša Štatkić, Nebojša Arsić, Nebojša Mitrović, Bojan Perović, Andrijana Jovanović

    Published 2025-04-01
    “…The first approach assumes that the starting rotor leakage reactance is equal to the stator leakage reactance, while the second considers them as distinct. Improvement of the algorithm consists of increasing the accuracy of the approximations of parameter changes on the rotor. …”
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  20. 1680

    Research on the Optimization of the PID Control Method for an EOD Robotic Manipulator Using the PSO Algorithm for BP Neural Networks by Yunkang Zhou, Xiaohui He, Faming Shao, Xiangpo Zhang

    Published 2024-10-01
    “…This study proposes a PID control strategy optimized by the particle swarm optimization (PSO) algorithm for a backpropagation (BP) neural network and simulates the system’s step response for analysis. …”
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    Article