Antenna Optimization Design Based on Deep Gaussian Process Model by Xin-Yu Zhang, Yu-Bo Tian, Xie Zheng

“…In this network, GP is used to replace the fully connected layer of the CNN, the convolutional layer and the pooling layer of the CNN are used to reduce the dimension of the input parameters and GP is used to predict output, while particle swarm optimization (PSO) is used algorithm to optimize network structure parameters. …”
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Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Simulation results demonstrate the BWO-based strategy’s superior performance, reducing total objective cost to $2.54 million, outperforming genetic algorithm (GA) and particle swarm optimization (PSO) by 5.01% and 8.54% respectively. …”
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A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

“…Its master stage uses one out of three different algorithms—Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), or the Multi-Objective Ant Lion Optimizer (MOALO)—while the slave stage is always performed by a load flow analyzer. …”
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How Much Power Is Needed for RIS to Beat Relays? A Sustainability Framework by Mohammad Abualhayja'a, Mahmoud Wagih, Anthony Centeno, Muhammad Ali Imran, Lina Mohjazi

“…To address the optimisation problem effectively, we have developed a robust algorithm based on the particle swarm optimisation approach (PSO). …”
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Deep reinforcement learning-based resource joint optimization for millimeter-wave massive MIMO systems by LIU Qingli, LI Xiaoyu, LI Rui

“…Experimental results show that the proposed joint optimization method significantly improves the throughput and energy efficiency of the system compared with the single-stage all-digital precoding and hybrid precoding equal resource allocation methods and the particle swarm optimization-based resource allocation algorithm.…”
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Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…Therefore, in order to solve the AMT vibration monitoring problem and enhance the diagnostic efficiency, this study proposes an AMT fault diagnosis model based on particle swarm optimization (PSO) to optimize the parameters of wavelet packet transform (WPT) and support vector machine (SVM).The optimal vibration signal acquisition point is determined by finite element analysis to ensure high signal quality. …”
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Discrete Optimization on Truck-Drone Collaborative Transportation System for Delivering Medical Resources by Min Lin, Yuming Chen, Rui Han, Yao Chen

“…We show by experiments that the number of trucks has more significant impact on the optimal solution than the number of drones and the performance of hybrid particle swarm optimization is better than the performance of the other algorithms.…”
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Joint Optimization of Berths and Quay Cranes Considering Carbon Emissions: A Case Study of a Container Terminal in China by Houjun Lu, Xiao Lu

“…This study presents an integrated model that incorporates tidal factors into the joint optimization of berth and quay crane operations, addressing both service standards and emissions during port stays and crane activities, and further designs a PSO-GA hybrid algorithm, combining particle swarm optimization (PSO) with crossover and mutation operators from a genetic algorithm (GA), to enhance optimization accuracy and efficiency. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Based on the reconstructed data, traditional Support Vector Regression (SVR) models and SVR models optimized by the Grid Search Method (GSM) are constructed. Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
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Performance Optimization Method of Steam Generator Liquid Level Control Based on Hybrid Iterative Model Reconstruction by Xiaoyu Li, Xiangsong Kong, Changqing Shi, Jinguang Shi, Zean Yang

“…The method first constructs the initial dataset with a small-sample Latin-square experiment design and then builds two different fitting models, SVM and Kriging, based on the initial dataset respectively, under the hybrid model fusion idea. After that, the particle swarm optimization algorithm is used to calculate the optimal point of the current valid model, and the optimization process is controlled by establishing the iteration termination judgment based on the historical iteration data. …”
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Fatigue life prediction and stresses applicability of TBCs by the virtual S-N curve method by Changcheng Xie, Chao Ma, Changhao Wang, Yudong Yao, Pinbo Huang

“…Finally, the errors of different stresses for TBCs life prediction are analyzed in conjunction with the particle swarm algorithm, and the stress with the best applicability is identified and verified experimentally. …”
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Gray Wolf Optimizer With Communication Strategy Based on DV-Hop for Nodes Location of Wireless Sensor Networks by Dan Yu, Ting Yuan, Haiyin Qing, Wenwu Xie, Peng Zhu

“…The Adaptive Weight Mechanism dynamically adjusts positions during the weight update process, while the pronounced randomness and the mechanisms of Lévy Flight steps enhance information exchange among wolves, thereby improving convergence speed. Comprehensive experimental analyses on established benchmark functions have validated the efficacy of the IGWO-CS method, illustrating its competitiveness with other advanced algorithms such as the Ranking-based Adaptive Cuckoo Search (RACS) and Modified Particle Swarm Optimization (MPSO). …”
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Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…[Methods] Based on historical precipitation, temperature, and runoff sequences from the Yulongkashi River, a Convolutional Neural Network-Bidirectional Gated Recurrent Unit-Attention (CNN-BiGRU-Attention) model was developed. An Improved Particle Swarm Optimization (IPSO) algorithm was used to optimize this model, forming the IPSO-CNN-BiGRU-Attention hybrid model. …”
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ARIMA-Based Forecasting of Wastewater Flow Across Short to Long Time Horizons by Jiawen Ye, Xulai Meng, Haiying Wang, Qingdao Zhou, Siwei An, Tong An, Pooria Ghorbani Bam, Diego Rosso

“…Then, the Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO) algorithm, and Sparrow Search Algorithm (SSA) were used for optimization, with the WOA excelling in accuracy and stability. …”
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Capacity Optimization Configuration of a Bidirectional Reversible Centralized Electrohydrogen Coupling System by Xing FENG, Wei YANG, Anan ZHANG, Xi ZHANG, Qian LI, Xianzhang LEI

“…The solution is solved by combining particle swarm optimization algorithm and CPLEX solver. …”
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UHVDC Transmission Line Fault Identification Method Based on Generalized Regression Neural Network by XIE Jia, LIU Feng, KE Yanguo, YIN Zhen, RUAN Wei, YAO Jinming

“…Secondly, the chaos quantum particle swarm optimization (CQPSO) algorithm is used to optimize the parameters of the generalized regression neural network, form an ideal network model based on the principle of the lowest fitness function, and better learn the fault characteristics of the ultra-high voltage DC transmission line. …”
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Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis by Yang Qi, Zheng Shijin, Xie Suzhen, Feng Enmin

“…Subsequently, we develop an improved particle swarm optimization algorithm to solve this equivalent problem. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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Seismic Performance Assessment of Optimal Tandem-Based Tuned Mass Damper Inerters by Maziar Fahimi Farzam, Shahram Ajori, Himan Hojat Jalali, Rim Najmeddine

“…The optimum design of all the studied configurations was determined by the particle swarm optimization (PSO) algorithm. The evaluation of the performances included the effectiveness in the frequency domain and that of the norm and maximum reduction in the displacement and absolute acceleration in the time domain under 21 earthquake records with different characteristics. …”
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Research on power system transformation based on edge node technology under the background of carbon neutrality by LI Jin, GAO Hongliang, LIU Kemeng, XIE Hu

“…In each island, the improved particle swarm optimization algorithm is used to reasonably distribute the power tasks, forming a novel power system with the coordinated planning of source-network-load-storage as the core. …”
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