Optimal power flow using recent red-tailed hawk optimization algorithm by Ahmed M Nassef, Mohammad Ali Abdelkareem, Mohamed Louzazni

“…In addition, the results obtained from the suggested approach have been compared to those achieved by other modern and competitive metaheuristic optimization algorithms, such as particle swarm optimization (PSO), Coot bird's algorithm (COOT), salp swarm algorithm (SSA), Marin predator algorithm (MPA), and the jellyfish search optimizer (JSO). …”
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Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization by Pradeep Kumar Singh, Ali Basem, Rebwar Nasir Dara, Mohamed Shaban, Sarminah Samad, Raymond Ghandour, Ahmad Almadhor, Samah G. Babiker, Iskandar Shernazarov, Ibrahim A. Alsayer

“…To optimize the system's performance, an artificial neural network is integrated with a multi-objective particle swarm optimization algorithm to reduce computational time from approximately 16 h to 4 min. …”
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Economic feasibility assessment and parameter sensitivity analysis of rainwater harvesting systems in different climatic zones of China by Chonghua Xue, Feng Xiong, Junqi Li, Xiaojing Li, Jing Li, Yu Wang, Xiangyu Li, Ziyu Cui

“…Using the Infoworks ICM model, long-term simulations (30 years) were conducted to evaluate the economic advantages of rainwater utilization across these climate zones. The Particle Swarm Optimization (PSO) was employed to optimize the cistern volume by integrating Net Present Value (NPV) and Benefit Cost Ratio (BCR). …”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
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Experimental study and model prediction of the influence of different factors on the mechanical properties of saline clay by Hui Cheng, Lingkai Zhang, Chong Shi, Pei Pei Fan

“…The improved particle swarm optimization-support vector regression (PSO-SVR) model has high accuracy and general applicability. …”
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Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This study proposes a hybrid workflow for determining the locations of production wells during primary oil recovery using a multi-modal convolutional neural network (M-CNN) integrated with an evolutionary optimization algorithm. The particle swarm optimization algorithm provides the M-CNN with full-physics reservoir simulation results as learning data correlating an arbitrary well location and its cumulative oil production. …”
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Study on a cable jumper method for offshore floating photovoltaic systems with multiple floating bodies by Xiangyu KONG, Yangping SHAO, Qiang FU, Lujie YU, Hongbin LIU

“…In the first stage, trust-region particle swarm optimization is employed to determine the feasible solution region of the spanning scheme variables. …”
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Optimization design of an acoustic cover layer for a cylindrical cavity based on porous materials by Bohan ZHANG, Jili RONG, Xiuyan CHENG

“…In this study, a comprehensive investigation into the parameter fitting and acoustic performance optimization of porous materials is conducted, utilizing advanced physical models, multifluid impedance transfer theory, and particle swarm optimization algorithms. This research combines experimental approaches, including impedance tube experiments, with numerical methods, such as acoustic finite element analysis, to enhance the noise control capabilities of porous materials. …”
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In situ real-time measurement for electron spin polarization in atomic spin gyroscopes by Feng Li, Haoying Pang, Zhuo Wang, Wenfeng Fan, Min Zhang, Zehua Liu, Jiahang Li, Bodong Qin, Xinxiu Zhou, Xusheng Lei, Ruigang Wang

“…This paper addresses this gap by developing a model for pump laser propagation within the vapor cell and proposing an Euler-particle swarm optimization (PSO) algorithm to estimate the model’s unknown parameters. …”
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Target Detection Using Fused Unidentical Photonics-Based LFM Sub-Band Radar Signals With an Adaptive Feed Forward Network Equalizer by Bikash Nakarmi, S. M. Rezwanul Islam, Hum Nath Parajuli, Ikechi Augustine Ukaegbu, Aigerim Ashimbayeva, Carlo Molardi, T. D. Subash, Xiangchuan Wang, Shilong Pan

“…Time-frequency analysis (TFA) was used to obtain sub-bandgap signals of 0.12 GHz, 0.56 GHz, and 1.25 GHz which are coherently fused using the FFNE with a particle swarm optimization (PSO) algorithm to optimize complex-valued weights. …”
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HHO–LSSVM prediction model of blast casting muck pile morphology based on Gaussian distribution by Ning MA, Li MA, Yinda LI, Tianxiang LI, Sen YANG, Fuming LIU, You ZHOU, Xiaomin WANG, Qifeng ZHANG, Mengbo LI

“…And the Gaussian distribution model combined with the HHO–LSSVM algorithm was used to predict the shape of the blast casting muck pile, compare the accuracy of the LSSVM, Particle Swarm Optimization (PSO) optimized Least Squares Support Vector Machine, and Genetic Algorithm (GA) optimized BP neural network models, at the same time, compare the predicted blast casting muck pile morphology with the actual blasting muck pile morphology. …”
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A comparative analysis of five land surface temperature downscaling methods in plateau mountainous areas by Ju Wang, Ju Wang, Ju Wang, Bo-Hui Tang, Bo-Hui Tang, Bo-Hui Tang, Bo-Hui Tang, Xinming Zhu, Xinming Zhu, Xinming Zhu, Dong Fan, Dong Fan, Dong Fan, Menghua Li, Menghua Li, Menghua Li, Junyi Chen, Junyi Chen, Junyi Chen

“…Three machine learning models, including Back Propagation (BP) Neural Network, random forest (RF), and extreme gradient boosting (XGBoost), and two classic single-factor linear regression models (DisTrad and TsHARP) were compared. Particle Swarm Optimization (PSO) was introduced to optimize hyperparameters of three machine learning methods. …”
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Spectral optimization of supercontinuum shaping using metaheuristic algorithms, a comparative study by Mathilde Hary, Teemu Koivisto, Sara Lukasik, John M. Dudley, Goëry Genty

“…We report here an experimental study of supercontinuum spectral shaping by tuning the phase of the input pulses, different optimization approaches including a genetic algorithm, particle swarm optimizer, and simulated annealing. We find that the genetic algorithm and particle swarm optimizer are more robust and perform better, with the particle swarm optimizer converging faster. …”
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A Novel PSO Model Based on Simulating Human Social Communication Behavior by Yanmin Liu, Ben Niu

“…In order to solve the complicated multimodal problems, this paper presents a variant of particle swarm optimizer (PSO) based on the simulation of the human social communication behavior (HSCPSO). …”
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Design of a Robust Coordinated Power Oscillation Damper for Use with Large-Scale Wind Energy System Connected to a Multimachine Power System by Paul Kabiru, Keren Kaberere, Stanley Kamau

“…A hybrid optimization algorithm based on the grey wolf optimizer (GWO) and particle swarm optimizer (PSO) is applied for parameter optimization of the damping controllers considering a multiobjective eigenvalue-based optimization problem. …”
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Energy and Wake effects Optimization of Offshore Wind Farm using PSO algorithm by Ouhdan Mahmoud, Ait Madi Abdessalam, Hassoine Mohammed Amine

“…To tackle this problem, the research has developed a multi-objective optimization framework in Python that shows the Pareto front, which illustrates the trade-off between wake effects and (AEP) by using a particle swarming optimization (PSO) algorithm. The proposed multi-objective optimization framework offers a disciplined way to balance energy production and wake loss, which advances the offshore wind farm design. …”
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A Real-Time and Closed-Loop Control Algorithm for Cascaded Multilevel Inverter Based on Artificial Neural Network by Libing Wang, Chengxiong Mao, Dan Wang, Jiming Lu, Junfeng Zhang, Xun Chen

“…In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC) algorithm is employed to minimize the total harmonic distortion (THD) and generate the optimal switching angles offline. …”
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A Universal Source DC–DC Boost Converter for PEMFC-Fed EV Systems With Optimization-Based MPPT Controller by C. H. Hussaian Basha, Shaik Rafikiran, Ezzeddine Touti, Besma Bechir Graba, Mouloud Aoudia

“…However, the fuel stack’s energy production is nonlinear and its operational point varies concerning the fuel stack device operating temperature. The particle swarm optimized adaptive network-based fuzzy inference system (PSO-ANFIS) is proposed in this work to find the operational point of the fuel cell network. …”
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Allocation and control of multi-devices voltage regulation in distribution systems via rough set theory and grasshopper algorithm: A practical study by Abdullah M. Elsayed, Ali M. El-Rifaie, Marwa F. Areed, Abdullah M. Shaheen, Mohamed Osman Atallah

“…Results show reductions in energy losses, enhanced voltage profiles, and maximized cost savings, substantiating the proposed method's effectiveness compared to traditional approaches such as the standard GOA, well-known Particle Swarm Optimizer (PSO) technique, Honey Badger Algorithm (HBA) and Tunicate Swarm Algorithm (TSA). …”
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