Optimal Operation of Droop Control in Microgrids Using Different Techniques Optimization: Review by Ruqaya Majeed Kareem

“…These techniques include Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO), Grasshopper Optimization Algorithm (GOA), and Salp Swarm Algorithm (SSA)…”
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Intelligent Fault Diagnosis of Aeroengine Sensors Using Improved Pattern Gradient Spectrum Entropy by Huihui Li, Linfeng Gou, Hua Zheng, Huacong Li

“…Then, we improved PGSE to use particle swarm optimization algorithm to adaptively optimize the influencing parameters (scale factor λ), so that the obtained spectral entropy graph can better match the CNN. …”
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Optimization of a two-stage emergency logistics system considering public psychological risk perception under earthquake disaster by Huawei Yang, Pan Zhang, Peiwen Zhang, Chenxing Zhang, Xuxian Yan

“…Based on the modified prospect theory framework, this article replaces the sufficiency and shortage of demand with gains and losses to optimize the resource allocation policy. Thirdly, Particle Swarm Optimization (PSO) is used to improve the Sparrow Search Algorithm (SSA) for further model solving. …”
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Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network by Luxin Jiang, Xiaohui Wang

“…In the evaluation of teaching quality, aiming at the shortcomings of slow convergence of BP neural network and easy to fall into local optimum, an online teaching quality evaluation model based on analytic hierarchy process (AHP) and particle swarm optimization BP neural network (PSO-BP) is proposed. …”
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Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Cat Swarm Optimization by Kuan-Cheng Lin, Yi-Hung Huang, Jason C. Hung, Yung-Tso Lin

“…Previous studies have indicated that CSO algorithms outperform other well-known metaheuristics, such as genetic algorithms and particle swarm optimization. This study presents a modified version of cat swarm optimization (MCSO), capable of improving search efficiency within the problem space. …”
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Development of a Driving Cycle for Fuzhou Using K-Means and AMPSO by Minrui Zhao, Hongni Gao, Qi Han, Jiaang Ge, Wei Wang, Jue Qu

“…On that basis, the K-means clustering method is used to cluster the dimensionally reduced data, and the adaptive mutation particle swarm optimization (AMPSO) algorithm is employed to select the optimal fragments from candidate fragments to develop a driving cycle. …”
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Vibration Reliability Analysis of Aeroengine Rotor Based on Intelligent Neural Network Modeling Framework by Jia-Qi Liu, Yun-Wen Feng, Cheng Lu, Wei-Huang Pan, Da Teng

“…INNMF is based on the artificial neural network (ANN) algorithm through improved particle swarm optimization (PSO) algorithm and Bayesian Regularization (BR) optimization. …”
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Thermal Diffusivity, Moisture Diffusivity, and Color Change of Codonopsis javanica with the Support of the Ultrasound for Drying by Xuan-Quang Nguyen, Anh-Duc Le, Ngoc-Phuong Nguyen, Hay Nguyen

“…Based on theoretical calculations, experimental data, and the particle swarm optimization (PSO) algorithm, the coefficient of thermal diffusion was determined in the range of 1.01–1.36 × 10−7 m2/s, and the coefficient of moisture diffusion is in the range of 3.2–6.7 × 10−10 m2/s. …”
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Joint Trajectory Planning of Space Modular Reconfigurable Satellites Based on Kinematic Model by Jiping An, Xinhong Li, Zhibin Zhang, Wanxin Man, Guohui Zhang

“…This paper investigates the application of particle swarm optimization (PSO) algorithm to plan joint trajectories of the space modular reconfigurable satellite (SMRS). …”
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Toward Enhancing the Energy Efficiency and Minimizing the SLA Violations in Cloud Data Centers by E. I. Elsedimy, Fahad Algarni

“…In this paper, an effective multiobjective algorithm based on Particle Swarm Optimization (PSO) technique for the VMP problem, referred to as VMPMOPSO, is proposed. …”
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Multi-stage adaptive speed control with torque ripple optimization for a switched reluctance motor in electric vehicle applications by Youness Boumaalif, Hamid Ouadi, Fouad Giri

“…In this context, a two-stage optimization strategy is proposed. Using the particle swarm optimization (PSO) technique, the first stage computes in offline mode, a first estimate of the optimal parameters of the SRM current reference signal. …”
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Reliability-Based Fatigue Life Prediction for Complex Structure with Time-Varying Surrogate Modeling by Lu-Kai Song, Guang-Chen Bai, Cheng-Wei Fei, Jie Wen

“…To improve the computational efficiency and accuracy of reliability-based fatigue life prediction for complex structure, a time-varying particle swarm optimization- (PSO-) based general regression neural network (GRNN) surrogate model (called as TV/PSO-GRNN) is developed. …”
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Energy Management Strategy for Direct Current Microgrids with Consideration of Photovoltaic Power Tracking Optimization by Fudong Li, Zonghao Shi, Zhihao Zhu, Yongjun Gan

“…Firstly, a hybrid algorithm for power tracking control is formed by incorporating the Particle Swarm Optimization (PSO) algorithm into the variable step-size Incremental Conductance (INC) method, thereby optimizing the maximum power point tracking control system of the photovoltaic system. …”
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Comparative Study of Population-based Metaheuristic Algorithms in Case Study of DNA Sequence Assembly by Lala Septem Riza, Yudi Prasetyo, Muhammad Iqbal Zain, Herbert Siregar, Rani Megasari, Topik Hidayat, Diah Kusumawaty, Miftahurrahma Rosyda

“…The algorithms used in this study include the Honey Badger Algorithm (HBA), Levy Flight Distribution (LFD), African Vultures Optimization Algorithm (AVOA), and Particle Swarm Optimization (PSO). Overall, AVOA has the best results where it can produce the most total overlap, where the most overlap is 49952 in the dataset with length 750 and coverage 25. …”
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Optimizing cut order planning: A comparative study of heuristics, metaheuristics, and MILP algorithms by Sharif Al-Mahmud, Jose Alejandro Cano, Emiro Antonio Campo, Stephan Weyers

“…Comparative analysis shows that Particle Swarm Optimization (PSO) outperforms GA, especially for small and medium-sized problems. …”
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Migration and mutation (MeTa) hybrid trained ANN for dynamic spectrum access in wireless body area network by Geoffrey Eappen, Shankar T, Rajesh A

“…Compared to particle swarm optimization (PSO)-ANN, classical ANN, and energy detection-based spectrum sensing techniques, the MeTa NN shows detection probability improvements of 9%, 16%, and 37% respectively.…”
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Low voltage user power internet of things monitoring system based on LoRa wireless technology by Xiao Wang, Wei Zhao, Xixian Niu

“…Additionally, an optimization model based on a particle swarm optimization algorithm and backpropagation neural network for optimizing base station positioning and channel quality evaluation is proposed. …”
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Data-Driven Approaches for Diagnosis of Incipient Faults in Cutting Arms of the Roadheader by Qiang Liu, Songyong Liu, Qianjin Dai, Xiao Yu, Daoxiang Teng, Ming Wei

“…In this study, four machine learning tools (the back-propagation neural network based on genetic algorithm optimization, the naive Bayes based on genetic algorithm optimization, the support vector machines based on particle swarm optimization, and the support vector machines based on dynamic cuckoo) are applied to address the challenge in the IFDI of cutting arms. …”
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Exploring the Teaching Mode of English Audiovisual Speaking in Multimedia Network Environment by Shunlan Wang

“…To address the problem of low recognition rate of English pronunciation, this study proposes a sound recognition algorithm based on adaptive particle swarm optimization (PSO) matching pursuit (MP) sparse decomposition. …”
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An optimizated additional damping control for suppressing ultra‐low frequency oscillation suppression based on SVC by Huabo Shi, Chengwei Fan, Xueyang Zeng, Gang Chen, Baorui Chen, Zhen Chen

“…Consequently, a parameter optimization design method for SVC additional damping control is proposed, it is modelled as the optimization problem of damping ratio in ULFO mode under multi‐operation conditions, which is solved by a particle swarm optimization algorithm. Finally, the effectiveness of the designed SVC additional damping controller is verified in the improved four‐machine two‐area power system and the actual power grid in China.…”
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