Optimal D-STATCOM placement and sizing using a novel bird swarm operated exploitation of elephant herd algorithm by V. Tejaswini, D. Susitra

“…In the 33-bus system at hour 14, the BSOEEH model achieved optimal results, surpassing established methods by significant margins: 1.06% superior to Grey Wolf Optimizer (GWO), 1.02% superior to Whale Optimization Algorithm (WOA), 1.02% superior to the GWO-WOA hybrid model, 0.13% superior to Elephant Herding Optimization (EHO), and 0.93% superior to Backtracking Search Algorithm (BSA). …”
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Quantum Selection for Genetic Algorithms Applied to Electromagnetic Design Problems by Gabriel F. Martinez, Alessandro Niccolai, Eleonora L. Zich, Riccardo E. Zich

“…A genetic algorithm with a quantum selection operator that applies high selection pressure while preserving selection diversity is introduced. …”
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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

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A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base by Huishan Song, Yanbin Yuan, Yuhe Wang, Jianbai Yang, Hang Luo, Shiming Li

Subjects: “…chaotic mapping adaptive whale optimization algorithm (WOA)…”
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Research on the Optimization of the PID Control Method for an EOD Robotic Manipulator Using the PSO Algorithm for BP Neural Networks by Yunkang Zhou, Xiaohui He, Faming Shao, Xiangpo Zhang

“…Simulation results indicate that compared to traditional BP+PID control, genetic algorithm (GA)+PID control, and whale optimization algorithm (WOA)-BP+PID control, the PSO-BP+PID algorithm control rapidly tunes the PID control parameters K_p, K_i, and K_d. …”
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The Bregman Modified Second APG Method for DC Optimization Problems by Lumiao Wang, Ziye Liu, Chunguang Liu

“…To address this limitation, researchers often employ Bregman distance as an alternative to Euclidean distance in existing DC algorithms. While this substitution relaxes the requirements on DC functions, it simultaneously introduces greater complexity in theoretical analysis. …”
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Optimized and Routed Wiring Harness Based on Zonal Clustering Concept Using AI in the Automotive Industry by Md Sanowar Hossain, Hafiz Abdul Quddus, Ziya Cevahir, Alexander Jesser

“…A methodology integrating K-means clustering with dynamic grid-based routing algorithms (A* and Bresenham’s line algorithm) is applied to optimize the wiring harness layout across the vehicle’s zones, covering six key domains (comfort, chassis, drive assist, infotainment, system, and powertrain). …”
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Prediction of Anthocyanin Content in Purple-Leaf Lettuce Based on Spectral Features and Optimized Extreme Learning Machine Algorithm by Chunhui Liu, Haiye Yu, Yucheng Liu, Lei Zhang, Dawei Li, Junhe Zhang, Xiaokai Li, Yuanyuan Sui

“…Finally, dung beetle optimization (DBO), subtraction-average-based optimization (SABO), and the whale optimization algorithm (WOA) optimized the extreme learning machine (ELM) for modeling. …”
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Smart Energy Strategy for AC Microgrids to Enhance Economic Performance in Grid-Connected and Standalone Operations: A Gray Wolf Optimizer Approach by Sebastian Lobos-Cornejo, Luis Fernando Grisales-Noreña, Fabio Andrade, Oscar Danilo Montoya, Daniel Sanin-Villa

“…To assess performance, 100 independent runs per method were conducted, comparing GWO against particle swarm optimization (PSO) and genetic algorithms (GAs). Statistical analysis confirmed that GWO achieved the lowest operational costs (USD 3299.39 in grid-connected mode and USD 11,367.76 in islanded mode), the highest solution stability (0.19% standard deviation), and superior voltage regulation. …”
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Investigation and optimal design of band gap tunability in fractal phononic crystals by Yang Shuai, Yin Jia-Hao, Zhu Xiao-Jing, Wang Kai, Zhang Shi-ke, Cao Lu, Guo Peng-Yu, Liu Yong

“…Furthermore, this study employs genetic algorithm optimization to achieve the maximum band gap width at different frequencies, enhancing the practical value of fractal phononic crystals in engineering applications. …”
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Prediction of Interest Rate Using Artificial Neural Network and Novel Meta-Heuristic Algorithms by Milad Shahvaroughi Farahani

“…The results show that Whale Optimization Algorithm (WOA) performed better than other methods along with less error.…”
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Application of Artificial Intelligence with Ant Colony Algorithm in construction projects schedule by Kiana Ahghari

“…So useMethodology of Scheduling of Projects with Artificial Intelligence and with the Approach of Ant Colony Algorithm for Organizations MethodOptimal and practical among other methods. …”
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Optimizing the Design of TES Tanks for Thermal Energy Storage Applications Through an Integrated Biomimetic-Genetic Algorithm Approach by Nadiya Mehraj, Carles Mateu, Gabriel Zsembinszki, Luisa F. Cabeza

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GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization by Jinghui Jiang, Dongjoon Kim, Bohyoung Kim, Yeong-Gil Shin

“…Our proposed Codebook Genetic Algorithm (CGA) selectively optimizes these underutilized tokens by applying genetic operations to enhance their representation capability while maintaining the well-learned features of frequently used tokens. …”
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Reliability Analysis of Three-Dimensional Slopes Considering the Soil Spatial Variability Based on Particle Swarm Optimization Algorithm by Xin Chen, Jiale Xu, Yukuai Wan, Rong Yang, Jiewen Sun, Di Wu

“…This paper presents a new algorithm for assessing the reliability of three-dimensional (3D) slope stability considering the spatial variability of soil based on the Particle Swarm Optimization (PSO) algorithm. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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A genetic algorithm approach to green vehicle routing: Optimizing vehicle allocation and route planning for perishable products by Hayati Mukti Asih, Raden Achmad Chairdino Leuveano, Dhimas Arief Dharmawan, Ardiansyah Ardiansyah

“…Utilizing a Genetic Algorithm (GA), the model demonstrates its effectiveness in achieving near-optimal solutions that balance economic, environmental, and quality-focused goals. …”
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An interior proximal gradient method for nonconvex optimization by De Marchi, Alberto, Themelis, Andreas

“…While traditional IP methods cannot cope with nonsmooth objective functions and proximal algorithms cannot handle complicated constraints, their combined usage is shown to successfully compensate the respective shortcomings. …”
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Optimization Algorithm of Adaptive Dual-layer Search Path Planning Based on Left-hand Traffic Rules in Mines by HUANG Jiade, LIU Yong, HU Yunqing, MEI Wenqing

“…This paper introduces an optimization algorithm for adaptive dual-layer search path planning based on the left-hand traffic rules in mining areas, aiming to improve the navigation performance of mine trucks within these areas while ensuring the path safety and the real-time planning. …”
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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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