Research on Collaborative Optimization Method of CCHP Regional Integrated Energy System Based on Improved Multivariate Universe Algorithm by Dahai Xu, Changle Yu, Wenwen Li, Su Zhang, Zhengda Li, Zhihui Qu, Pengtao Li, Xingfan Han

“…A case study conducted in a representative northern region yielded the following experimental results: When compared with both the traditional particle swarm algorithm and an improved version of it, the CCHP-type integrated energy system optimized using the enhanced multi-objective multiverse algorithm reduced operating costs by 7.98% and carbon dioxide emissions by 12%, relative to the original system. …”
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Predictive Control for an Ankle Rehabilitation Robot Using Differential Evolution Optimization Algorithm-Based Fuzzy NARX Model by Shenglong Xie, Haiming Zhong, Yuntang Li, Su'an Xu, Wenyuan Liu, Shiyuan Bian, Shiwu Zhang

“…Then, the optimization of objective function is compared with genetic algorithm and particle swarm optimization. …”
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Prediction of barite scale formation and inhibition in hydrocarbon reservoirs using AI modeling: Focus on different optimization algorithms by Ouafa Belkacem, Ahmed Rezrazi, Kamel Aizi, Lokmane Abdelouahed, Maamar Laidi, Abdelhafid Touil, Leila Cherifi, Salah Hanini

“…Innovative intelligent models, including Random Forest (RF), k-nearest Neighbors (KNN), Extreme Learning Machine (ELM), Support Vector Regression (SVR), Decision Trees (DT), and Multilayer Perceptron (MLP), were developed and optimized for this purpose. Notably, the MLP and SVR models were enhanced through training with the particle swarm optimization algorithm (PSO) and data augmentation techniques. …”
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A new sliding mode control strategy to improve active power management in a laboratory scale microgrid by Oscar Gonzales-Zurita, Jean-Michel Clairand, Guillermo Escrivá-Escrivá

“…The research was conducted in a PSCAD environment, where a real industrial SPVSI with PI control was emulated and then optimized using the SMC-2. The employed tuning method was the particle swarm optimization (PSO) technique. …”
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Hybridization and Optimization of Bio and Nature-Inspired Metaheuristic Techniques of Beacon Nodes Scheduling for Localization in Underwater IoT Networks by Umar Draz, Tariq Ali, Sana Yasin, Muhammad Hasanain Chaudary, Muhammad Ayaz, El-Hadi M. Aggoune, Isha Yasin

“…The hybridization techniques such as Elephant Herding Optimization (EHO) with Genetic Algorithm (GA), Firefly Algorithm (FA), Levy Firefly Algorithm (LFA), Bacterial Foraging Algorithm (BFA), and Binary Particle Swarm Optimization (BPSO) are used for optimization. …”
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A Comparison of the Black Hole Algorithm Against Conventional Training Strategies for Neural Networks by Péter Veres

“…This study presents a comparative analysis of four training algorithms, Backpropagation, Genetic Algorithm, Black-hole Algorithm, and Particle Swarm Optimization, evaluated across both classification and regression tasks. …”
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Enhancing workflow efficiency with a modified Firefly Algorithm for hybrid cloud edge environments by Deafallah Alsadie, Musleh Alsulami

“…In this study, we evaluate various scheduling algorithms, emphasizing the Modified Firefly Optimization Algorithm (ModFOA) and comparing it with established methods such as Ant Colony Optimization (ACO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). …”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…The meta-heuristic algorithms employed for fine-tuning the ANN's weight and bias parameters include the Genetic Algorithm (GA), Multi-Verse Optimizer (MVO), Moth Flame Optimization (MFO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Advanced Grey Wolf Optimizer (AGWO), Biogeography-Based Optimization (BBO), and Particle Swarm Optimization with Grey Wolf Optimizer (PSOGWO). …”
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A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems by Shuaijie Wang, Xin Guan, Shu Liu

“…In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to optimize photovoltaic hybrid energy storage scheduling, improving global search and convergence speed, is discussed. …”
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Integrated Reliability Assessment and Optimal Reconfiguration of Islanded Microgrids Under Load Growth Using Fick’s Law Optimization Algorithm and Long Short-Term Memory Tec... by Hieu M. Pham, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan, Corina Barbalata

“…To address the complex, mixed-variable nature of the reconfiguration problem, the Fick’s Law Optimization (FLO) algorithm is proposed. The FLO algorithm is compared with other metaheuristic algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) algorithm, Non-dominated Sorting Genetic Algorithm II (NSGA-II), Artificial Bee Colony (ABC) algorithm, Grey Wolf Optimizer (GWO) algorithm, Equilibrium Optimizer (EO) algorithm, Runge-Kutta Optimizer (RUN) algorithm, and Honey Badger Algorithms (HBA) demonstrating superior performance in convergence speed, exploration–exploitation balance, and global optimality. …”
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Optimizing laser powder bed fusion parameters for enhanced hardness of Ti6Al4V alloys: A comparative analysis of metaheuristic algorithms for process parameter optimization by Praveenkumar V, Vijaykumar S. Jatti, Saiyathibrahim A, Praveen Kumar D, Murali Krishnan R, Vinaykumar S. Jatti, A. Johnson Santhosh

“…A comparative assessment of six metaheuristic algorithms, such as the JAYA algorithm, Cohort Intelligence (CI), Particle Swarm Optimization (PSO), Teaching-Learning-Based Optimization (TLBO), Genetic Algorithm (GA), and Simulated Annealing (SA), was performed for LPBF parameter optimization. …”
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A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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Multistep PV power forecasting using deep learning models and the reptile search algorithm by Sameer Al-Dahidi, Hussein Alahmer, Bilal Rinchi, Abdullah Bani-Abdullah, Mohammad Alrbai, Osama Ayadi, Loiy Al-Ghussain

“…Further, RSA was benchmarked against the Whale Optimization Algorithm (WOA), Gray Wolf Optimizer (GWO), and Constrained Particle Swarm Optimization (CPSO), and consistently outperformed all three across all models in both forecasting horizons. …”
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Maximizing Energy Output of Photovoltaic Systems: Hybrid PSO-GWO-CS Optimization Approach by Hassan S. Ahmed, Ahmed J. Abid, Adel A. Obed, Ameer L. Saleh, Reheel J. Hassoon

“…This study aims to address these challenges by combining cuckoo search (CS), gray wolf optimization (GWO), and particle swarm optimization (PSO) to enhance MPPT performance. …”
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Low Capillary Elastic Flow Model Optimization Using the Lattice Boltzmann Method and Non-Dominated Sorting Genetic Algorithm by Yaqi Hou, Wei Zhang, Jiahua Hu, Feiyu Gao, Xuexue Zong

“…The hyperparameters of the machine learning model are optimized using the particle swarm algorithm. In contrast, the non-dominated sorting genetic algorithm (NSGA-II) is incorporated to optimize bubble lengths and stability. …”
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A novel pigeon-inspired optimization with QUasi-Affine TRansformation evolutionary algorithm for DV-Hop in wireless sensor networks by Xiao-Xue Sun, Jeng-Shyang Pan, Shu-Chuan Chu, Pei Hu, Ai-Qing Tian

“…According to the experimental results, they demonstrate that it is more outstanding than the Pigeon-Inspired Optimization algorithm, the QUasi-Affine TRansformation Evolutionary algorithm, and particle swarm optimization algorithm. …”
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Flow Control of Tractor Multi-Channel Hydraulic Tester Based on AMESim and PSO-Optimized Fuzzy-PID by Qinglun Li, Xuefeng Bai, Yang Lu, Xiaoting Deng, Zhixiong Lu

“…To improve the dynamic response, linearity, and control accuracy of the YYSCT-250-3 tractor multi-circuit hydraulic output power tester, this study develops a particle swarm optimization (PSO)-tuned fuzzy-proportional–integral–derivative (Fuzzy-PID) control strategy. …”
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Large Data Oriented to Image Information Fusion Spark and Improved Fruit Fly Optimization Based on the Density Clustering Algorithm by Yanfang Zhang

“…Then, a hybrid fruit fly particle swarm algorithm based on a genetic optimization mechanism is proposed to achieve dynamic optimization seeking for parameters in local clustering to improve the clustering effect of local clustering. …”
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Optimal Allocation of Hybrid Renewable Distributed Generation with Battery Energy Storage System Using MOEA/D-DRA Algorithm by P. Pon Ragothama Priya, S. Baskar, S. Tamil Selvi, C. K. Babulal

“…Simulation studies are conducted on IEEE 33-node and TNEB 84-node Radial Distribution Systems (RDSs), comparing results with the Rider Optimization Algorithm (ROA) and Hybrid Nelder Mead-Particle Swarm Optimization (HNMPSO) respectively. …”
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Ultrahigh-Dimensional Model and Optimization Algorithm for Resource Allocation in Large-Scale Intelligent D2D Communication System by Minxin Liang, Jiandong Liu, Jinrui Tang, Ruoli Tang

“…In addition, a novel evolutionary algorithm called the cooperatively coevolving particle swarm optimization with variable-grouping (VGCC-PSO) is developed, in which a novel mutation operation is introduced for ensuring fast satisfaction of constraints. …”
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