The optimization of low Earth orbit satellite constellation visibility with genetic algorithm for improved navigation potential by Chao Qin, Yanbin Gao, Yihuan Wang

“…Abstract To tackle visibility optimization challenges in Low Earth Orbit satellite constellations, this study proposed an enhanced framework based on an adaptive parallel Genetic Algorithm (GA). The aim was to improve both navigation accuracy and dynamic robustness. …”
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Low-carbon economic optimization for flexible DC distribution networks based on the hiking optimization algorithm by Ke Wu, Yuefa Guo, Ke Wang, Zhenliang Chen

“…In addition, a comparative study with traditional particle swarm and genetic algorithms demonstrates that the HOA, by incorporating adaptive mechanisms for both search space resolution and speed adjustment, enhances both global exploration and local exploitation, effectively avoiding local optima traps. …”
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MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…This model integrates pre-processing techniques and employs the Tuna Swarm Optimization (TSO) Algorithm for feature selection in executing multi-label disease prediction. …”
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Back analysis of geomechanical parameters based on a data augmentation algorithm and machine learning technique by Hui Li, Weizhong Chen, Xianjun Tan

“…Accurate geomechanical parameters are key factors for stability evaluation, disaster forecasting, structural design, and supporting optimization. …”
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A modified perturb and observe MPPT algorithm for PEMFC with rapid convergence and low power oscillation by Resat Celikel, Omur Aydogmus, Musa Yilmaz

“…A comparative analysis is conducted against the conventional P&O and optimization-based MPPT algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Genetic Algorithm (GA). …”
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An Adaptive Layering Dual-Parameter Regularization Inversion Method for an Improved Giant Trevally Optimizer Algorithm by Chao Tan, Menghao Sun, Wei Liu, Wenrui Tan, Xiaoling Zhang, Chengang Zhu, Da Li

“…Subsequently, the current model parameters of the inversion objective function are optimized using the Giant Trevally Optimizer (GTO) algorithm, improved by the Particle Swarm Optimization (PSO) algorithm. …”
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Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques by S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, R. Gandhi Raj, K. Kalaivani, N. Kopperundevi, M. Chinnadurai, M. Nuthal Srinivasan, L. Ramachandran

“…To select the best optimization model for MPPT under PSC, the nature-inspired dragonfly algorithm (DA), moth flame optimization algorithm (MFOA), grasshopper optimization algorithm (GOA), and salp swarm optimization algorithm (SSOA) are used in this work to evaluate the tracking efficiency (TE) of the solar PV systems. …”
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Integrating particle swarm optimization with backtracking search optimization feature extraction with two-dimensional convolutional neural network and attention-based stacked bidir... by Jyotirmayee Rautaray, Sangram Panigrahi, Ajit Kumar Nayak

“…It is compared against five advanced techniques: particle swarm optimization (PSO), Cat Swarm Optimization (CSO), long short-term memory (LSTM) with convolutional neural networks (LSTM-CNN), support vector regression (SVR), bee swarm algorithm (BSA), ant colony optimization (ACO) and the firefly algorithm (FFA). …”
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GLOPS: A Hybrid Approach for Enhanced Scheduling in Cloud Computing Environments via Machine Learning-Based Process Prediction by Syed Abu Ammar Muhammad Zarif, Layla Kader Suma, Md. Sadat Rahman, Md. Motaharul Islam, Phuoc Hung Pham, Phong Dung Thi Nguyen, Nguyen Thanh Binh

“…However, early predictions would seem futile without efficient scheduling, which is why the article further proposes Global and Local Optimized Preemptive Scheduling (GLOPS), an enhanced metaheuristic scheduling algorithm employing Particle Swarm Optimization and Simulated Annealing. …”
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Dynamic performance improvement of oscillating water column wave energy conversion system using optimal walrus optimization algorithm-based control strategy by Habiba A. ElDemery, Hany M. Hasanien, Mohammed Alharbi, Chuanyu Sun, Dina A. Zaky

“…The proposed WOA-based PI controller design’s effectiveness is evaluated by comparing its simulation results with that obtained from using genetic algorithm (GA), grey wolf (GWO), particle swarm (PWO), and harmony search (HS) optimization-based PI controllers under symmetrical and unsymmetrical faults. …”
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Multi-UAV Search and Rescue with Enhanced A∗ Algorithm Path Planning in 3D Environment by Yuwen Du

“…Further, we evaluate the algorithm via simulating the task assignment algorithm and path-planning algorithm of a 3D map and 2D map. …”
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Prediction and evaluation of residual life of casing with corrosion defects by JIA Aoyin, QIAN Liqin, WANG Jie, YANG Jingwei, WU Yaokun, WEI Mingji

“…The particle swarm optimization-gaussian process regression （PSO-GPR) algorithm was employed to construct a predictive model for casing corrosion rates.ResultsIntegration of the two models, the evaluation of the residual life of casings with corrosion defects was completed, it has theoretical guidance significance for the prevention and management of corroded casings in oil field operations.…”
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ROLLING BEARING WEAK FAULT FEATURE EXTRACTION METHOD WITH ALIF⁃NLM by WANG Ying, SONG YuBo, ZHU DaPeng

“…Aiming at the problem that the early weak fault feature was difficult to extract of rolling bearing under the strong noise background,combined with the advantages of adaptive local iterative filter(ALIF)and non⁃local means(NLM)method,an ALIF⁃NLM bearing weak fault feature extraction method was proposed.Firstly,a weighted kurtosis⁃energy ratio criterion was constructed to filter the intrinsic mode function(IMF)components of the ALIF decomposition and reconstruct the signal.Secondly,the minimum energy entropy⁃kurtosis ratio index was constructed by combining the sensitivity of kurtosis to the impact signal with the evaluation performance of energy entropy to the uniformity and complexity of signal energy distribution,and using this index as the fitness function,the adaptive selection of parameter combinations in NLM method was realized by particle swarm optimization(PSO)algorithm.Finally,the fault feature of the reconstructed signal was extracted with the adaptive NLM.The simulation and experimental results show that this method can effectively extract the weak fault feature information of rolling bearing under the strong noise background.…”
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Using crafted features and polar bear optimization algorithm for short-term electric load forecast system by Mansi Bhatnagar, Gregor Rozinaj, Radoslav Vargic

“…PBO was compared with commonly used optimization algorithms like particle swarm optimization (PSO) and genetic algorithm (GA). …”
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The close-open mixed-fleet electric vehicle routing problem by Themistoklis Stamadianos, Nikolaos A. Kyriakakis, Magdalene Marinaki, Yannis Marinakis

“…To solve large instances, three discrete optimization swarm intelligence algorithms are employed, alongside a Variable Neighborhood Search algorithm. …”
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Optimum load computation of a piezoelectric-based energy harvester by Andrés Felipe Gomez-Casseres

“…Methodology: Such a model is obtained using the Particle Swarm Optimization (PSO) algorithm, selected due to the sim- plicity of its implementation. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Performance evaluation will use AUC with an alpha value of 0.050. …”
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AI-based routing algorithms improve energy efficiency, latency, and data reliability in wireless sensor networks by Rahul Priyadarshi, Ravi Ranjan Kumar, Rakesh Ranjan, Padarti Vijaya Kumar

“…Abstract This paper proposes a modular Artificial Intelligence (AI)-based routing framework for Wireless Sensor Networks (WSNs) that integrates reinforcement learning (RL), supervised learning, and swarm intelligence techniques such as genetic algorithms (GA) and particle swarm optimization (PSO). …”
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Multistage Threshold Segmentation Method Based on Improved Electric Eel Foraging Optimization by Yunlong Hu, Liangkuan Zhu, Hongyang Zhao

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A dual-adaptive stochastic reinforcement chimp optimization algorithm for fire detection and multidimensional problem solving by Ziyang Zhang, Lingye Tan, Diego Martín, Leren Qian, Mohammad Khishe, Pradeep Jangir

“…Abstract Chimp optimization algorithm (CHOA) is a recently developed nature-inspired technique that mimics the swarm intelligence of chimpanzee colonies. …”
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