Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…Based on the multi-scale mean-shift clustering algorithm, Adaptive Kernel Density Estimation (AKDE) is introduced to map density to bandwidth, achieving adaptive adjustment of clustering bandwidth while reducing computational resources and improving cloud hierarchy. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…We evaluated our approach on twelve datasets from various fields, achieving an average F1 score improvement of 1.5% while reducing the feature set size by 54.5%. …”
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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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Study on Trajectory Planning for Polishing Free-Form Surfaces of XY-3-RPS Hybrid Robot by Xiaozong Song, Junfeng An, Xingwu Ma

“…This paper proposes an improved trajectory planning method based on curvature characteristics, incorporating dynamic partitioning and boundary smoothing algorithms. …”
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Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques by Poonam Saroha, Gopal Singh, Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Majed Alsafyani, Hamed Alsufyani

“…These dynamics are difficult for traditional systems to handle, but new developments in reinforcement learning and optimization may be able to help. The paper introduces a novel Demand Response (DR) method that integrates a Self-Adaptive Puma Optimizer Algorithm (SAPOA) with a Multi-Objective Deep Q-Network (MO-DQN), improving smart home energy consumption, cost, and user preferences management. …”
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Artificial-Intelligence-Based Energy Management Strategies for Hybrid Electric Vehicles: A Comprehensive Review by Bin Huang, Wenbin Yu, Minrui Ma, Xiaoxu Wei, Guangya Wang

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Dynamic parking space allocation at urban scale: Problem formulation and resolution by Hanae Errousso, Jihane El Ouadi, El Arbi Abdellaoui Alaoui, Siham Benhadou

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Nonlinear Narrowband Active Noise Control for Tractors Based on a Momentum-Enhanced Volterra Filter by Tao Zhang, Zhixuan Guan, Shuai Zhang, Kai Song, Boyan Huang

“…The proposed approach integrates the nonlinear representation power of the Volterra filter with a momentum optimization mechanism to enhance convergence speed while maintaining robust steady-state accuracy. …”
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Revolutionizing RPAS logistics and reducing CO2 emissions with advanced RPAS technology for delivery systems by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Richard C. Millar, Robert Walter Meyer

“…These integrations significantly decrease battery consumption in Remotely Piloted Aircraft Systems (RPAS) and lower transportation costs, while also optimizing delivery times, reducing operational risks, and minimizing CO2 emissions. …”
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Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller by Monika Gupta, P. M. Tiwari, R. K. Viral, Ashish Shrivastava, Basem Abu Zneid, Iryna Hunko

“…Abstract This paper introduces a robust and adaptive control framework that integrates a Proportional–Integral–Derivative (PID) controller with the bio-inspired Grey Wolf Optimization (GWO) algorithm for real-time tuning of controller parameters in grid-connected photovoltaic (PV) inverter systems. …”
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Fuzzy Optimized Attention Network with Multi-Instance Deep Learning (FOAN-MIDL) for Alzheimer’s Disease Diagnosis with Structural Magnetic Resonance Imaging (sMRI) by Afnan M. Alhassan, Nouf I. Altmami

“…<b>Results:</b> An attention technique to estimate the weight of every case is presented: the fuzzy salp swarm algorithm (FSSA). The swarming actions of salps in oceans serve as the inspiration for the FSSA. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The algorithm divides the population into two parts, using the non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization algorithm (MOPSO) for solving, with improvements to enhance the algorithm’s performance. …”
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Advanced Planning Systems in Production Planning Control: An Ethical and Sustainable Perspective in Fashion Sector by Martina De Giovanni, Mariangela Lazoi, Romeo Bandinelli, Virginia Fani

“…The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635e-001, while the average optimal value is 6.83551939e-001. …”
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Honeyword Generation Using a Proposed Discrete Salp Swarm Algorithm by Yasser A. Yasser, Ahmed T. Sadiq, Wasim AlHamdani

“…This work will present a novel honeyword generation method that uses a proposed discrete salp swarm algorithm. The salp swarm algorithm (SSA) is a bio-inspired metaheuristic optimization algorithm that imitates the swarming behavior of salps in their natural environment. …”
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Modified Swarm-Based Artificial Intelligence Optimization for Optimal Coordination of Directional Overcurrent Relays in Power System by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Herie Park

“…The coordination of directional overcurrent relays (DOCRs) plays a critical role in ensuring the reliability and robustness of modern electrical power protection systems. Achieving optimal relay coordination in multi-loop power networks is a complex optimization challenge requiring the minimization of relay operating times and achieve optimal tuning of time dial settings (TDS) and plug settings (PS) while considering the impact of DG integration. …”
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A Novel Traffic Scheduling Algorithm for Multi-CQF Using Mixed Integer Programming and Variable Neighborhood Search Genetic Algorithm in Time-Sensitive Networking by Cheng Wang, Zhiquan Lin, Yuhao Zhao, Fen Hu, Zhan Huan

“…MIP quickly seeks out the optimal scheduling solution for small-traffic TSN networks using branch-and-bound and linear programming techniques, while the VNS-GA improves efficiency and performance for large-traffic ones by continuously adjusting the search neighborhood strategy. …”
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Adaptive dynamic ϵ-simulated annealing algorithm for tumor immunotherapy by Xiaoyan Sun, Xiaoyan Sun, Ying Jiang

“…When applied to the ITIT model, the algorithm successfully identified optimal drug dosing schedules that significantly reduced simulated tumor burden—from ~1500 to below 500 cells—while maintaining treatment within physiologically acceptable limits.DiscussionUnlike traditional metaheuristics such as PSO or GA, which are less suited for constraint-rich, dynamic ODE-based systems, ADϵSA offers structural advantages in trajectory feasibility and adaptive convergence. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…The study compared the performance of five optimization algorithms: Grey Wolf Optimizer (GWO), Artificial Hummingbird Algorithm (AHA), Tunicate Swarm Algorithm (TSA), War Strategy Algorithm (WSA), and Moth flam optimizer (MFO). …”
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