Risk Assessment of Supplier R&D Investment Based on Improved BP Neural Network by Yinghua Song, Xiaoyan Sang, Zhe Wang, Hongqian Xu

“…By leveraging the ability of particle swarm optimization (PSO), whale optimization algorithm (WOA), and genetic algorithm (GA) to search for global optimal solutions, the BP neural network is improved to avoid becoming trapped in local optimal solutions and enhance the model’s generalization ability. …”
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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction by Babu Kumar, Radhakrishnan Soundararajan, Kanimozhi Natesan, Roobini Maridhas Santhi

“…This approach involves many rounds of data sorting for decreasing noise, thresholding an ECG difference signal by examining the time interval between QRS, and then comparing relative magnitudes to identify the area of interval processing to evaluate accuracy results. In order to choose the best features, a modified chicken swarm optimization algorithm (MCSO) was proposed. …”
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Multidimensional Resource Task Scheduling Based on Particle Swarm Optimization in Edge Computing by Zhonglu Zou, Zhuxin Zhai, Xin Yan, Zilin You, Liming Chen

“…The proposed approach enables the simultaneous scheduling of multiple tasks while iteratively adjusting the inertia weight and learning factors in the discrete particle swarm optimization (DPSO) algorithm. Experimental results with different types of applications show that, compared to the baseline scheduling methods, the proposed strategy can flexibly adapt to the varying demands of different task types and effectively reduce the imbalance in the utilization of multi-dimensional cluster resources. …”
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A hybrid ensemble framework with particle swarm optimization for network anomaly detection by Narinder Verma, Neerendra Kumar, Gourav Kumar, Kuljeet Singh

“…We propose an adaptive particle swarm optimization (PSO)-optimized ensemble learning framework tailored to address these challenges in modern IDS applications. …”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

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A corrective direction particle swarm optimization for large-scale multi-objective optimization by Weichao Chen, Ziyang Li, Xue Li

“…Abstract In multi-objective optimization, Large-Scale Multi-Objective Optimization Problems (LSMOPs) involve a large number of decision variables and present significant challenges in finding satisfactory results with a limited number of function evaluations. To address this issue, a Corrective Direction Particle Swarm Optimization (CDPSO) is proposed for large-scale multi-objective optimization in this paper. …”
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Automated Pruning Framework for Large Language Models Using Combinatorial Optimization by Patcharapol Ratsapa, Kundjanasith Thonglek, Chantana Chantrapornchai, Kohei Ichikawa

“…Two techniques were particularly studied, i.e., particle swarm optimization (PSO) and whale optimization algorithm (WOA). …”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…The evaluation indices solved by the improved algorithm were optimized to varying degrees. …”
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Binary Particle Swarm Optimization with Manta Ray Foraging Learning Strategies for High-Dimensional Feature Selection by Jianhua Liu, Yuxiang Chen, Shanglong Li

“…The proposed BPSO-MRFL algorithm was evaluated using 10 high-dimensional small-sample gene expression datasets. …”
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Entropy-Driven Global Best Selection in Particle Swarm Optimization for Many-Objective Software Package Restructuring by Amarjeet Prajapati, Anshu Parashar, null Sunita, Alok Mishra

“…It has been observed that these kinds of many-objective optimization problems (MaOPs) often pose several performance challenges to the traditional multi-objective optimization algorithms. To address the performance issue caused by the different types of MaOPs, recently, a variety of many-objective particle swarm optimization (MaOPSO) has been proposed. …”
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Mathematical modeling and optimization of the active suspension system of a 6x6 electric vehicle by Berk Aydoğan, Ahmet Yildiz

“…Three different methods were used for optimization: Genetic Algorithm (GA), Particle Swarm Optimization (PSE) and Differential Evolution (DE) Optimization. …”
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An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

“…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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Research on Capacitated Multi-Ship Replenishment Path Planning Problem Based on the Synergistic Hybrid Optimization Algorithm by Lin Yang, Qinghua Chen, Junjie Mu, Tangying Liu, Xiaoxiao Li, Shuxiang Cai

“…The proposed methodology employs a three-stage optimization framework: (1) initial path generation via parallel execution of the CW and ACO; (2) population initialization for the GA by strategically combining optimal solutions from ACO and the CW with randomized solutions; (3) iterative refinement using an enhanced GA featuring an embedded evolutionary reversal operation for local intensification. To evaluate performance, the SHOA is benchmarked against ACO, the GA, the particle swarm optimization algorithm, and the simulated annealing algorithm for the capacitated vehicle routing problem. …”
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A Comparison of Metaheuristic Algorithms for Structural Optimization: Performance and Efficiency Analysis by Saeedeh Ghaemifard, Amin Ghannadiasl

“…The findings confirm the effectiveness of the algorithms, with particle swarm optimization and social network search frequently delivering superior results across most problem sets.…”
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Sensitivity Analysis of a CPAM Inverse Algorithm for Composite Laminates Characterization by Farshid Masoumi, Ahmad Ghasemi Ghalebahman

“…An inverse method based on particle swarm optimization algorithm is further provided using MATLAB software. …”
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A parallel multi-objective genetic algorithm for scheduling scientific workflows in cloud computing by Muhammad Sardaraz, Muhammad Tahir

“…The proposed algorithm is evaluated with benchmark datasets and comparative results with the standard genetic algorithm, particle swarm optimization, and specialized scheduler are presented. …”
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Investigation of technoeconomic optimization for sizing renewable energy systems using metaheuristic and hybrid algorithms by Bouafia Mohammed, El Fathi Amine, El Akchioui Nabil

“…This study focuses on optimizing grid-connected Hybrid Renewable Energy Systems (HRES) in Morocco using technoeconomic approaches, including metaheuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO) and Artificial Bee Colony (ABC) and hybrid methods combining these latter with Modified Marquardt Gradient Descent (MGD). …”
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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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Generic multidimensional economic environmental operation of power systems using equilibrium optimization algorithm by Mohamed T. Mouwafi, Adel A. Abou El-Ela, Amany A. El-Hamoly, Ragab A. El-Sehiemy

“…The numerical results obtained by the proposed EOA are compared with other optimization techniques such as grey wolf optimization, particle swarm optimization (PSO), differential evolution algorithm, and other optimization techniques in the literature. …”
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