Multiscale Modeling and Reconstruction of Joint Motion: Finite Element Optimization Based on Particle Swarm Algorithm by Jiaju Zhu, Zhong Zhang, Runnan Liu, Meixue Ren, Guodong Ma

“…High-resolution CT and MRI scans of the knee joint were utilized to construct an accurate 3D reconstruction model, while the particle swarm algorithm was implemented to optimize joint positioning. …”
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Optimal Design of Linear Quadratic Regulator for Vehicle Suspension System Based on Bacterial Memetic Algorithm by Bala Abdullahi Magaji, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…The BMA adopts control parameters that support biological attraction, reproduction, and elimination-dispersal processes to accelerate the search and enhance the program’s stability. By using an algorithm, it explores several parts of space and improves its value to determine the optimal setting for the control gains. …”
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Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms by Milad Shahvaroughi Farahani

“…The results show that Whale Optimization Algorithm (WOA) performed better than other methods along with less error.…”
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Application of Artificial Intelligence with Ant Colony Algorithm in construction projects schedule by Kiana Ahghari

“…So useMethodology of Scheduling of Projects with Artificial Intelligence and with the Approach of Ant Colony Algorithm for Organizations MethodOptimal and practical among other methods. …”
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An efficient swarm evolution algorithm with probability learning for the black and white coloring problem by Zhiqiang Zhang, Li Zhang, Xiujun Zhang

“…Furthermore, crossover operation, perturbation operation, and tabu search strategy improve the search ability of the algorithm, while evolutionary operation with probability learning mechanism increases the probability of the algorithm finding better solutions. …”
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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization by Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

“…This computational study, based on real historical data, verifies the effectiveness of the proposed model and algorithm. The results demonstrate notable improvements in fleet efficiency and environmental performance, increasing profitability by 4.38% while maintaining favorable CII ratings. …”
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Aerodynamic Optimization Method for Propeller Airfoil Based on DBO-BP and NSWOA by Changjing Guo, Zhiling Xu, Xiaoyan Yang, Hao Li

“…To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). …”
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Developing an Optimization Model for Minimizing Solid Waste Collection Costs by Muciz Özcan, Semih Cengiz, Mehmet Şen

“…The Simulated Annealing (SA) algorithm, one of the heuristic optimization techniques used to identify the best solutions to complicated problems, is employed to solve the routing problem of solid waste collection vehicles in this study. …”
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines by Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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Optimization of a reinforced concrete structure subjected to dynamic wind action by Jherbyson Williams Silva Brito, Let�cia Fleck Fadel Miguel

“…This work proposes a methodology to optimize a reinforced concrete structure. For this, the Whale Optimization Algorithm (WOA) algorithm was used, an algorithm from the group of metaheuristic algorithms, which presents an easy computational implementation. …”
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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
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Optimizing high-speed train tracking intervals with an improved multi-objective grey wolf by Lin Yue, Meng Wang, Peng Wang, Jinchao Mu

“…To achieve multi-objective dynamic optimization, a novel train tracking operation calculation method is proposed, utilizing the improved grey wolf optimization algorithm (MOGWO). …”
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Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…By balancing exploration-exploitation using CSA while adapting search parameters through reinforcement learning, RL-CSA ensures scalability, improved DG utilization (98%), and better voltage stability (< 0.005 p.u.), making it a robust and intelligent alternative for modern smart grid optimization.…”
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An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems by Marwa M. Emam, Mohammed R. Saad, Mina Younan, Essam H. Houssein

“…The optimizers include the improved multi-operator differential evolution algorithm (IMODE), adaptive guided differential evolution algorithm (AGDE), whale optimization algorithm (WOA), grey wolf optimizer (GWO), sinh cosh optimizer (SCHO), RIME optimization algorithm (RIME), and the original EDO. …”
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Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
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Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

“…This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). …”
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Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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Estimation of the Angles of a Robotic Arm with 7-Free Degrees Using an Improved Hybrid ESSA Algorithm by Inayet Hakki Cizmeci, Adem Alpaslan Altun

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Particle Swarm Optimization on Parallel Computers for Improving the Performance of a Gait Recognition System by Shahla A. Abdulqader, Hasmek A. Krekorian

“…In recent years, the gait recognition (GR) using particle swarm optimization (PSO) algorithm (OSO) has been execute very fast and accurate with single computer, but with the appearance of parallel computing (PC), it was necessary to use this technique to improve the results of GR. …”
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