6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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Queen honey bee migration (QHBM) optimization for droop control on DC microgrid under load variation by Aripriharta Aripriharta, Mochammad Syarifudin Al Rasyid, Muhammad Cahyo Bagaskoro, Irham Fadlika, Sujito Sujito, Arif Nur Afandi, Saodah Omar, Norzanah Rosmin

“…Simulation results show that QHBM reaches an error of 0.8737 at the fourth iteration. The QHBM and PSO algorithms successfully optimized the performance of the DC microgrid under diverse loads, with QHBM converging in 5 iterations with an error of about 0.8737, and PSO in 40 iterations drawn error is 0.9 while keeping the current deviation less than 1.5 A and voltage error less than 0.5 V. …”
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From Fourier topology representation to optimal robot: evolution of an ultrahigh performance XYθ z nanopositioner by Zheng Lyu, Zilin Yang, Aiwu Zhou, Kang Tai, Guo Zhan Lum

“…Here we use a unique combination of kinematic analyses and evolutionary algorithms to determine our robot’s optimal geometry in which its structural topology is represented by Fourier basis functions. …”
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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

“…In this manuscript, an Underwater Object Detection and Classification Utilizing the Ensemble Deep Learning Approach and Hybrid Optimization Algorithms (UODC-EDLHOA) technique is developed. …”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

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Bio-Inspired Metaheuristics in Deep Learning for Brain Tumor Segmentation: A Decade of Advances and Future Directions by Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana, Wahyu Caesarendra, Nurul Huda

“…This review systematically examines developments from 2015 to 2025, focusing on the integration of nature-inspired optimization methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and novel hybrids including CJHBA and BioSwarmNet into deep learning-based brain tumor segmentation frameworks. …”
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Flexible Demand Side Management in Smart Cities: Integrating Diverse User Profiles and Multiple Objectives by Nuno Souza e Silva, Paulo Ferrão

“…Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. …”
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Decision-Making Model for Life Cycle Management of Aircraft Components by Igor Kabashkin, Vitaly Susanin

“…The optimization method on the base of genetic algorithm (GA) is employed to minimize total life cycle costs while maintaining component reliability within acceptable thresholds. …”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…To address this, we applied the Firefly Optimization Algorithm to fine-tune the hyperparameters of both the graph-based model and a CNN baseline for comparison. …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The prediction accuracy of the BP neural network optimized by particle swarm optimization is slightly better than that of the BP neural network optimized by genetic algorithm.…”
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Advancing Pile-Bearing Capacity Prediction with Meta-Heuristic Enhanced Specific ANFIS strategys by Zhongmiao Dang

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Advanced Design of Naval Ship Propulsion Systems Utilizing Battery-Diesel Generator Hybrid Electric Propulsion Systems by Youngnam Park, Heemoon Kim

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A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…In the third stage, Dijkstra’s algorithm is combined with GIS to optimize the bus routes, with a focus on accessibility and economy.Experimental results demonstrate that the THGO method can efficiently find the global optimal solution while satisfying constraints such as time windows, bus capacity, and road directionality. …”
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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…To address the multi-factor coupling, temporal dependency, and nonlinear complexity characteristics of concrete dam deformation, this paper proposed a hybrid prediction model integrating attention mechanisms, bidirectional long short-term memory (BiLSTM) networks, and sparrow search algorithm (SSA). The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…Dialysis session data from 758 patients collected between January 2016 and October 2019 were analyzed. Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. …”
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Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling by Ashraf Radaideh, Mu’men Bodoor, Ayman Al-Quraan

“…The performance of the optimal controller represented by a linear quadratic regulator is further enhanced using the whale optimization algorithm in a multiobjective optimization environment. …”
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Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

“…To further improve feature selection, we utilize the Chaotic Whale Optimization (ChWO) Algorithm, which optimally selects the most relevant attributes from the extracted features. …”
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Optimization of Laser-Induced Hybrid Hardening Process Based on Response Surface Methodology and WOA-BP Neural Network by Qunli Zhang, Jianan Ling, Zhijun Chen, Guolong Wu, Zexin Yu, Yangfan Wang, Jun Zhou, Jianhua Yao

“…This study uses Box–Behnken design (BBD) experiments to analyze key process parameters and develops response surface methodology (RSM) and whale-optimization-algorithm-optimized back-propagation neural network (WOA-BPNN) models for prediction and optimization. …”
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Evolved Motor Design Process to Reduce the Design Expense of Axial Flux Permanent Magnet Motor by Jong-Min Ahn, Dong-Kuk Lim, Min-Mo Koo

“…This paper proposes a design process that combines an initial electromagnetic design using analytical techniques with an optimal design based on a multi-objective optimization algorithm, aiming to reduce the design cost of an axial flux permanent magnet motor for urban air mobility traction. …”
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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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