Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
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An Adaptive 24 GHz PSO-Based Optimized VCO in Next-Generation Wireless Sensor Networks by Khizra Tariq, Unal Aras, Tahesin Samira Delwar, Muhammad Nadeem Ali, Yangwon Lee, Jee-Youl Ryu, Byung-Seo Kim

“…In this paper, the adaptive particle swarm optimization (PSO) algorithm incorporates adaptive scaling to speed up the optimization process. …”
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Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization by P. Nirmala, G. Ramkumar, Satyajeet Sahoo, G. Anitha, S. Ramesh, S. Agnes Shifani, Agegnehu Shara Shata

“…The impacts of various casting parameters of composites have been examined in detail. PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. …”
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Coordinated Optimization and Operational Strategy for Multi-type Energy Storage in Regional Integrated Energy Systems by Mingfei GAO, Zhonghe HAN, Bin ZHAO, Peng LI, Di WU

“…And then, by taking into account three objectives of economy, environment, and energy efficiency, the model was used to optimize the operational parameters of systems by utilizing the improved multi-objective particle swarm optimization (MOPSO) algorithm in conjunction with the TOPSIS method. …”
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Synthesis of the Sparse Uniform-Amplitude Concentric Ring Transmitting Array for Optimal Microwave Power Transmission by Hua-Wei Zhou, Xue-Xia Yang, Sajjad Rahim

“…This paper describes the synthesis method of the sparse uniform-amplitude transmitting array with concentric ring layout using particle swarm optimization (PSO) algorithm while keeping a higher BCE. …”
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Vibration Analysis and Optimization of Iron-Core Reactors Based on Fe-Based Soft Magnetic Composite Materials by Yangyang Ma, Wenle Song, Jie Gao, Yang Liu, Yilei Shang, Weimei Zhao, Fuyao Yang

“…The characteristic parameters of the improved model are identified using the particle swarm optimization–simulated annealing (PSO-SA) algorithm, with the identified root mean square error not exceeding 3.5, verifying the model’s accuracy. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…In multiple knapsack problems, LSGO variants reach a profit of 1925 units, exceeding Particle Swarm Optimization (PSO) (1850 units). For bin packing problems, the binary splitting strategy optimally minimizes bin usage, achieving 5 bins on the P04 dataset, while maintaining solution quality. …”
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Semi-analytical modeling and multi-objective optimization of horizontal-well deep borehole heat exchangers by Zhiwei Wang, Xuemei Zhang, Hui Zhang, Hangyu Liu, Shangkuan Yang, Zheng Qian, Jianguo Feng

“…Based on these insights, a particle swarm optimization (PSO) algorithm simultaneously explores pipe radius, horizontal-well length, working fluid flow rate and groundwater seepage velocity to maximize the objective function—the working fluid outlet temperature and minimize system costs. …”
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A Joint Optimization Model for Energy and Reserve Capacity Scheduling With the Integration of Variable Energy Resources by M. Wajahat Hassan, Thamer Alquthami, Ahmad H. Milyani, Ashfaq Ahmad, Muhammad Babar Rasheed

“…The proposed method is applied on the IEEE-standard 6-Bus system and particle swarm optimization (PSO) algorithm is used to solve the cost minimization objective function. …”
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Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…Feature selection (FS) was conducted using Binary version of Grey Wolf Optimizer (BGWO), Particle Swarm Optimization (BPSO), Whale Optimization Algorithm (BWAO), and a novel hybrid BPSO-BWAO approach to identify the most relevant features for AQI prediction. …”
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Optimization control strategy for active distribution areas with E-SOP considering energy storage characteristics by Weixu YU, Yewen WEI, Peng YUAN, Sijia ZHANG, Zhipeng ZHOU, Jie ZHANG

“…This model is transformed into a second-order cone programming model using conic relaxation techniques and solved iteratively through a particle swarm optimization algorithm. Finally, simulations on an IEEE 33-node flexible interconnected system validate the effectiveness of the proposed strategy, and further simulations on an IEEE 69-node system confirm its applicability and superiority. …”
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Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification by Mohammed Hussain, Thaer Thaher, Mohamed Basel Almourad, Majdi Mafarja

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A multi-objective optimization framework for functional layer design in solid oxide electrolysis cells by Hassan Salihi, Kisung Lim, Neil Vaz, Sun Dong Kim, Hyunchul Ju

“…The MLP model, integrated with Particle Swarm Optimization, achieved a minimum cell voltage (Vcell) of 1.288 V at 1.0 A/cm2 in single-objective optimization, closely matching CFD simulation results (1.2883 V). …”
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A Hybrid PSO-GA Optimized Approach for COVID-19 Detection Using CT Scan by Abdelghany Fathy, Hatem Abdelkader, Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Amira Abdelatey

“…In the second step, a hybrid particle swarm optimization (PSO) and genetic algorithm (GA) optimized approach, called Hybrid PSO-GA, is developed and used to select the optimal features that can increase the accuracy of COVID-19 detection. …”
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Multi-strategy cooperative enhancement dung beetle optimizer and its application in obstacle avoidance navigation by Xiaojie Tang, Zhengyang He, Chengfen Jia

“…Abstract Path planning is a crucial component of unmanned driving systems designed to address the challenge of autonomous navigation. This article introduces a novel approach called the multi-strategy cooperative enhanced dung beetle optimization algorithm (RCDBO) and applies it to dispose of path planning issues. …”
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Prediction of Psychoacoustic Metrics Using Combination of Wavelet Packet Transform and an Optimized Artificial Neural Network by Mehdi POURSEIEDREZAEI, Ali LOGHMANI, Mehdi KESHMIRI

“…The proposed method extracts objective psychoacoustic metrics including loudness, sharpness, roughness, and tonality from sound samples, by using a special selection of multi-level nodes of the WPT combined with a trained ANN. The model is optimized using the particle swarm optimization (PSO) and the back propagation (BP) algorithms. …”
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Integrated Vibration Control of In-Wheel Motor-Suspensions Coupling System via Dynamics Parameter Optimization by Wei Wang, Mu Niu, Yuling Song

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Collision Avoidance for Unmanned Surface Vehicles in Multi-Ship Encounters Based on Analytic Hierarchy Process–Adaptive Differential Evolution Algorithm by Zhongming Xiao, Baoyi Hou, Jun Ning, Bin Lin, Zhengjiang Liu

“…The proposed AHP-ADE algorithm was compared with the improved particle swarm algorithm, and the performance of the algorithm was comprehensively evaluated using safety, economy, and operational efficiency. …”
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Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

“…Traditional optimization techniques, such as genetic algorithms, particle swarm optimization, and ant colony optimization, have demonstrated adaptability in node placement but struggle with real-time self-learning capabilities, requiring frequent retraining to handle continuously changing conditions. …”
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Multi-Objective Optimization of Independent Automotive Suspension by AI and Quantum Approaches: A Systematic Review by Muhammad Waqas Arshad, Stefano Lodi, David Q. Liu

“…Some of the most common computational methodologies, which are Genetic Algorithms, Particle Swarm Optimization, and Gradient Descent, are discussed in this paper along with the new quantum computing techniques such as Gate-Based quantum computing and Quantum Annealing (QA). …”
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