Improved Data Transmission Scheme of Network Coding Based on Access Point Optimization in VANET by Zhe Yang, Lingzhi Li, Wenqiang Yao, Kaisheng Xu, Dongxin Tang

“…In this paper, an access point optimization method is proposed based on particle swarm optimization algorithm. …”
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Analysis and Optimization on Transmission Accuracy of Shoulder Joint Reducer for an Upper Limb Rehabilitation Robot by Zou Shuaidong, Wang Guangjian, Xie Guanghui, Hou Jingming, Yang Renqiang, Sun Fanwei

“…Based on the analytical model of shoulder joint transmission accuracy, the output torque fluctuation caused by transmission error is analyzed and particle swarm optimization algorithm is adopted to optimize transmission accuracy under the condition of constant machining accuracy, so as to improve the output torque fluctuation caused by transmission error of the shoulder joint of the upper limb rehabilitation robot to avoid the secondary injury of the patients.…”
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An Intelligent Optimization System Using Neural Networks and Soft Computing for the FMM Etching Process by Wen-Chin Chen, An-Xuan Ngo, Jun-Fu Zhong

“…The system integrates advanced optimization techniques, including the Taguchi method, analysis of variance (ANOVA), back-propagation neural network (BPNN), and a hybrid particle swarm optimization–genetic algorithm (PSO-GA) approach to identify optimal process parameters. …”
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An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. …”
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A Parameter Optimization Method and Evaluation of Aggregation Ability of Thermostatically controlled Load Model by WANG Hongtao, ZHANG Liwei, MU Gang

“…The model approximates the working characteristics of the thermostatically controlled loads (TCL). The particle swarm optimization algorithm is used to optimize the parameters in the model, and the error is corrected by the linear regression equation. …”
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A Cluster-based Optimal Scheduling Strategy for Electric Vehicles Considering User Participation by HAN Yan, DING Xiying, CHENG Kun, LI Xiaodong

“…Considering both peak shaving effect and user economic benefits, an improved particle swarm optimization algorithm is proposed to optimize the power participating in peak shaving. …”
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Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance by Qi Tang, Huan Wang

“…To solve the model, we design an improved particle swarm algorithm combining genetic operators, crossover operators and elite retention operator. …”
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An Enhanced Distribution System Performance with Optimization Techniques for Location of Electrical Vehicle Charging Stations by Sainadh Singh Kshatri, Venkata Anjani Kumar G, Chilakapati Lenin Babu, Palepu Suresh Babu

“…The effectiveness of the GWO-based approach is rigorously evaluated using the IEEE-33 bus system, a standard benchmark in distribution system analysis. The GWO algorithm's performance is evaluated in comparison to that of the prevalent Particle Swarm Optimization (PSO) methodology. …”
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Optimization of Central Pattern Generator-Based Torque-Stiffness-Controlled Dynamic Bipedal Walking by William Suliman, Chadi Albitar, Lama Hassan

“…This reduction enables the employment of the particle swarm algorithm to find the optimal values of these parameters which lead to different solutions with different performance criteria. …”
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An Opportunistic Array Beamforming Technique Based on Binary Multiobjective Wind Driven Optimization Method by Zhenkai Zhang, Sana Salous, Hailin Li, Yubo Tian

“…The simulation results show that the proposed method outperforms conventional particle swarm optimization (PSO) in the optimal beamforming by achieving more reduction in the sidelobe level and saving more runtime.…”
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A Pragmatic Optimization Method for Motor Train Set Assignment and Maintenance Scheduling Problem by Jian Li, Boliang Lin, Zhongkai Wang, Lei Chen, Jiaxi Wang

“…A heuristic solution strategy based on particle swarm optimization is also proposed to solve the model. …”
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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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Optimizing energy and load management in island microgrids for enhancing resilience against resource interruptions by Majid Hosseina, Mahmoud Samiei Moghaddam, Amir Hassannia

“…The superiority of MOMFA over conventional optimization techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) is validated through simulations on a realistic 33-node microgrid under various renewable energy outage scenarios. …”
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Load forecasting of microgrid based on an adaptive cuckoo search optimization improved neural network by Liping Fan, Pengju Yang

“…The mean absolute percentage error (MAPE) of the ICS-BP forecasting model was 1.13%, which was very close to an ideal prediction model, and was 52.3, 32.8, and 42.3% lower than that of conventional BP, cuckoo search improved BP, and particle swarm optimization improved BP, respectively, and the root mean square error (RMSE), mean absolute error (MAE), and mean square error (MSE) of ICS-BP were reduced by 75.6, 70.6, and 94.0%, respectively, compared to conventional BP. …”
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Optimal Sizing and Placement of Renewable Energy Sources in Power System Connected Multi-Microgrids by Amel Brik, Nour EL Yakine Kouba, Ahmed Amine Ladjici

“…The objective was to minimize the total active power losses with the assurance of a good voltage profile. The application of Particle Swarm Optimization (PSO) on the IEEE 33-bus network shows the validity of the proposed algorithm to minimize power losses and incorporate optimal micro-grid in the appropriate buses, which gives the optimal capacity and location of microgrid in the distribution network.…”
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Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-parametric Tests by Milena Gajić, Sanela Arsić, Jordan Radosavljević, Miroljub Jevtić, Bojan Perović, Dardan Klimenta, Miloš Milovanović

“…This paper proposes a new metahaeuristic algorithm named particle swarm optimization and chaotic gravitational search algorithm (PSO-CGSA) for solving the combined economic and emission dispatch (CEED) problem. …”
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An improved synergistic dual-layer feature selection algorithm with two type classifier for efficient intrusion detection in IoT environment by G Logeswari, K Thangaramya, M Selvi, J. Deepika Roselind

“…A robust feature selection subsystem, employing Synergistic Dual-Layer Feature Selection (SDFC) algorithm, combines statistical methods, such as mutual information and variance thresholding, with advanced model-based techniques, including Support Vector Machine (SVM) with Recursive Feature Elimination (RFE) and Particle Swarm Optimization (PSO) are employed to identify the most relevant features. …”
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Optimization Research on Energy Management Strategies and Powertrain Parameters for Plug-In Hybrid Electric Buses by Lufeng Wang, Juanying Zhou, Jianyou Zhao

“…Subsequent to this, a combined multi-layer powertrain optimization method based on Genetic Algorithm-Optimal Adaptive Control of Motor Efficiency-Particle Swarm Optimization (GOP) is proposed. …”
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Carbon Quota Allocation Prediction for Power Grids Using PSO-Optimized Neural Networks by Yixin Xu, Yanli Sun, Yina Teng, Shanglai Liu, Shiyu Ji, Zhen Zou, Yang Yu

“…The proposed model employs a hybrid of the gray forecasting model-particle swarm optimization-enhanced back-propagation neural network (GM-PSO-BPNN) for forecasting and allocating the total carbon quota. …”
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Optimizing Power System Performance: The Significance of Placement and Sizing of Battery Energy Storage Systems by Harith B. Hussien, Ahmed J. Abid, Naseer M. Yasin, Ameer L. Saleh, Hayder Jasim Habil

“…To do this, two meta-heuristic optimization algorithms are suggested in this paper, Particle Swarm Optimization (PSO) and Dragonfly Algorithm (DA). …”
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