Optimized Intelligent Localization Through Mathematical Modeling and Crow Search Algorithms by Tamer Ramadan Badawy, Nesreen I. Ziedan

“…However, existing localization methods still fall short of achieving the precision needed for certain high-demand applications. The proposed algorithm is designed to enhance localization accuracy by integrating mathematical modeling with the Crow Search Algorithm (CSA). …”
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Modeling and Optimization of Cable Production Scheduling by Incorporating an Ant Colony Algorithm by Changbiao Zhu, Chongxin Wang, Zhonghua Ni, Xiaojun Liu, Abbas Raza

“…Applying an ant colony (ACO) algorithm to solve the production scheduling problem achieved the intelligent scheduling and optimization of production tasks. …”
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Omni-Channel Product Distribution Network Design by Using the Improved Particle Swarm Optimization Algorithm by Si Zhang, Heying Zhu, Xia Li, Yan Wang

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A Novel Network Optimization Scheme Based on Anti-Flocking and Improved Nash Equilibrium Algorithm by Tianjun Wang, Shuchang Zhang, Lishan Liu, Duanpo Wu, Xinyu Jin, Shuwei Cen, Bing Fan

“…In this paper, a novel network optimization scheme based on anti-flocking model and improved Nash Equilibrium (NE) algorithm is proposed by studying the problem of dynamic UAV deployment and backhaul transmission. …”
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Optimization of Human Resource Performance Management System Based on Improved R-Means Clustering Algorithm by Rui Wang

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An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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Application of Optimization Algorithms in Voter Service Module Allocation by Edgar Jardón, Marcelo Romero, José-Raymundo Marcial-Romero

“…Allocation models are essential tools for optimally distributing client requests across multiple services under defined restrictions and objective functions. …”
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An improved meta-heuristic algorithm to optimize the fractional-order controller for an industrial manipulator with a parallelogram structure by Nazila Nikdel

“…Therefore, this article pursues two main objectives: 1) controlling the robotic system by presenting a method based on fractional-order calculus so that it can control the system despite its complexity and non-linearity, 2) presenting the meta-heuristic algorithm "Improved Grey Wolf" to optimize the system response.Methodology: First, the mathematical model of the robot is presented based on Lagrange rules, and then the fractional-order calculus is used to design the controller. …”
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Control Strategy of a Rotating Power Flow Controller Based on an Improved Hybrid Particle Swarm Optimization Algorithm by Ziyang Zhang, Jiaoxin Jia, Waseem Aslam, Abubakar Siddique, Fahad R. Albogamy

“…Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. …”
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Improving frequency stability in grid-forming inverters with adaptive model predictive control and novel COA-jDE optimized reinforcement learning by Muhammad Zubair Yameen, Zhigang Lu, Fayez F. M. El-Sousy, Waqar Younis, Baqar Ali Zardari, Abdul Khalique Junejo

“…The offline phase employs a novel Hybrid Crayfish Optimization and Self-Adaptive Differential Evolution Algorithm (COA-jDE) to minimize the cost function $$U_{offline}$$ , deriving optimal control parameters (Q, R) before real-time deployment. …”
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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

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Improved Model Predictive Control Algorithm for the Path Tracking Control of Ship Autonomous Berthing by Chunyu Song, Xiaomin Guo, Jianghua Sui

“…To address the issues of path tracking accuracy and control stability in autonomous ship berthing, an improved algorithm combining nonlinear model predictive control (NMPC) and convolutional neural networks (CNNs) is proposed in this paper. …”
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Reliability Optimization of Structural Deformation with Improved Support Vector Regression Model by Zheng-Zheng Zhu, Yun-Wen Feng, Cheng Lu, Cheng-Wei Fei

“…To improve the reliability optimization of turbine blades, this paper proposes a novel machine learning-based reliability optimization approach, named improved support vector regression (SR) model (ISRM) method, by fusing artificial bee colony (ABC), traditional SR model, and multipopulation genetic algorithm (MPGA). …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Besides, we propose an improved equilibrium optimizer (EO) approach whereby the previous EO is modified. …”
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Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

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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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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

“…For the prediction of VIV parameters, the Random Forest model is the most effective. The RMSE values of the improved optimal algorithm are 0.017, 0.026, and 0.295, and the R² values are 0.9421, 0.8875, and 0.9462. …”
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New Maps of Lunar Surface Oxide Abundances and Mg# Using an Optimized Ensemble Learning Algorithm by Chaofa Bian, Kefei Zhang, Yunzhao Wu, Suqin Wu, Yu Lu, Yabo Duan, Huajing Wu, Zhenxing Zhao, Wei Wu

“…In this study, multisource data, specifically KAGUYA multiband imager (MI) data and Diviner Christiansen feature (CF) products, referred to as MI-CF, combined with an ensemble learning algorithm optimized by improved particle swarm optimization (IPSO), were utilized to produce new maps of six oxides (FeO, TiO₂, Al₂O₃, CaO, MgO, and SiO₂) and Mg# at a resolution of 59 m/pixel within the Moon's 65° N/S range. …”
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Multiobjective Reactive Power Optimization Planning for Medium Voltage Distribution Networks Based on Improved Genetic Algorithm by Min Li, Juncheng Zhang, Jing Tan, Xiaohong Tan, Lingjie Tang

“…Therefore, a multiobjective reactive power optimization planning method for medium voltage distribution networks based on an improved genetic algorithm is studied. …”
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Electric load forecasting based on kernel extreme learning machine optimized by improved sparrow search algorithm by Diming Zhang, Yuchen Xu, Yuanjiang Li

“…The results show that the proposed model realizes an average improvement of 5.7% in the R2 metric compared to benchmark models. …”
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