Swarm Intelligence Algorithms for Optimization Problems a Survey of Recent Advances and Applications by Mande Smita Samrat, M Srinivasulu, Anand Sruthi, K Anuradha, Tiwari Mohit, U Esakkiammal

“…The responsiveness of SI algorithms to parameter configurations facilitates the development of adaptive methods that dynamically adjust parameters, while the demand for a better exploration-exploitation balance creates opportunity for development of convergence strategies that improve efficiency. …”
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SACWOM: Synergistic Adaptive Congestion Window Optimization Mechanism for Self-Clocked Algorithm by Haider Dhia Zubaydi, Ahmed Samir Jagmagji, Sandor Molnar

“…Phase II analysis shows up to 20.76-22.64% improvements with optimized configurations. Finally, Phase III, comprising 100 experiments, reveals SACWOM’s dynamic adaptability, achieving up to 50-70% improvements. …”
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Optimizing firefighting resilience in airports through genetic algorithms and decision-making frameworks by Yulong Zhu, Wei Tian, Xuhong Jia, Quanyi Liu

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Comparative Analysis of Optimization Algorithms to Enhance WPGSs Performance: Malaysia Case Study by Hussein Shutari, Taib Ibrahim, Nursyarizal Bin Mohd Nor, Hakim Abdulrab, Yahya Z. Alharthi, Mohammad Faridun Naim Tajuddin, Maveeya Baba

“…This outcome confirms the significant role of ODCSs in improving the efficiency and performance of WPGS under the mentioned challenges, while also revealing that their effectiveness varies depending on the precision of design established by the utilized optimization algorithm.…”
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Comparison of Energy Consumption Optimization in Sugar Factory Using Meta-Heuristic Algorithms by M. Boroun, M. Ghahderijani, A. A. Naseri, B. Beheshti

“…Energy flow were analyzed using MATLAB statistical software and the Equinonet database, with comparative optimization through genetic algorithms and imperialist competitive algorithms to identify efficiency improvements.Results and DiscussionThe results showed that, for the majority of indicators evaluated, the imperialist competitive algorithm outperformed the genetic algorithm in optimizing energy consumption. …”
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Benchmarking Metaheuristic Algorithms Against Optimization Techniques for Transportation Problem in Supply Chain Management by Felicia Lim Xin Ying, Suliadi Firdaus Sufahani

“…The research aims to explore the application of metaheuristic algorithms, with the Modified Distribution (MODI) method as the benchmark while employing the NorthWest Corner Method (NWCM) to obtain an initial feasible solution, to evaluate their performance in optimizing transportation problems. …”
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BDCOA: Wavefront Aberration Compensation Using Improved Swarm Intelligence for FSO Communication by Suhas Shankarnahalli Krishnegowda, Arvind Kumar Ganesh, Parameshachari Bidare Divakarachari, Veena Yadav Shankarappa, Nijaguna Gollara Siddappa

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An Improved KF-RBF Based Estimation Algorithm for Coverage Control with Unknown Density Function by Lei Zuo, Maode Yan, Yaoren Guo, Wenrui Ma

“…Compared with the other estimation algorithms, a novel sampling regulation mechanism is designed to improve the estimation performance and reduce the computational load. …”
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Recognition algorithm of piano playing music notes based on improved hidden Markov model by Ziwei Wang

“…The recognition process of piano playing music notes is affected by low-frequency components, resulting in suboptimal features that affect recognition accuracy. Therefore, an improved hidden Markov model based recognition algorithm for piano playing music notes is proposed. …”
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An improved sliding mode observer algorithm for PMSM based on deformable fuzzy neural network by Xiaolin Li, Na Liu, Juan Song, Yiyan Zhang

“…The findings suggest that the proposed algorithm enhances the accuracy of speed estimation and rotor position while optimizing the speed control performance of vector control system.…”
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Path Planning for Construction Robot Based on the Improved A* Algorithm and Building Information Modeling by Dejiang Wang, Bolong Liu, Haili Jiang, Panpan Liu

“…Finally, the improved A* algorithm is employed to perform path planning within the environment map generated from the BIM model, resulting in the generation of the optimal path. …”
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Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm by Anqi Xu, Hui Li, Yun Hong, Guoji Liu

“…To verify the effectiveness of the optimization, a 6v6 aircraft gaming simulation example is provided for comparison, and the experimental results show that the convergence speed of the optimized PW-PSO algorithm is 56.34% higher than that of the traditional PSO; therefore, the algorithm can improve the speed of decision-making while meeting the performance requirements.…”
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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization by Muhammad Suhail Shaikh, Chang Wang, Senlin Xie, Gengzhong Zheng, Xiaoqing Dong, Shuwei Qiu, Mohd Ashraf Ahmad, Saurav Raj

“…This study presents an Improved Chaotic Grey Wolf Optimization (ICGWO) algorithm to enhance WSN coverage and connectivity while addressing challenges like high deployment costs, limited coverage, and insufficient connectivity. …”
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Improved MobileVit deep learning algorithm based on thermal images to identify the water state in cotton by Kaijun Jin, Jihong Zhang, Ningning Liu, Miao Li, Zhanli Ma, Zhenhua Wang, Jinzhu Zhang, Feihu Yin

“…These enhancements aim to improve model performance while maintaining its compact size. …”
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GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation by Eman Mahmoud, Salem Alkhalaf, Tomonobu Senjyu, Masahiro Furukakoi, Ashraf Hemeida, Ghada Abozaid

“…However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. …”
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Application of GA-ACO Optimized BP Neural Network in Fault Diagnosis of Planetary Gearbox by Chang Gao, Zhongqing Yu, Qiang Zhou

“…Aiming at the problems of low fault recognition rate， slow convergence speed and difficult parameter selection in the process of fault diagnosis of planetary gearbox based on BP neural network improved by optimization algorithm， a GA-ACO algorithm is proposed to optimize the parameters of neural network. …”
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A Hybrid Whale Optimization Approach for Fast-Convergence Global Optimization by Athanasios Koulianos, Antonios Litke, Nikolaos K. Papadakis

“…In this paper, we introduce the Levy Flight-enhanced Whale Optimization Algorithm with Tabu Search elements (LWOATS), an innovative hybrid optimization approach that enhances the standard Whale Optimization Algorithm (WOA) with advanced local search techniques and elite solution management to improve performance on global optimization problems. …”
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Bio-inspired swarm intelligence for enhanced real-time aerial tracking: integrating whale optimization and grey wolf optimizer algorithms by GaoFeng Han

“…Abstract To address the decline in real-time tracking performance of moving targets in multi-UAV systems caused by uneven search coverage and low cooperation efficiency, the WGWO (Whale-Grey Wolf Optimization) model is proposed. The UAV swarm optimizes its flight paths using the spiral predation strategy of the WOA (Whale Optimization Algorithm) while employing a Kalman filter to process sensor data. …”
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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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Smooth Optimised A*-Guided DWA for Mobile Robot Path Planning by Liling Cao, Lei Tang, Shouqi Cao, Qing Sun, Guofeng Zhou

“…In mobile robot path planning, the traditional A* algorithm suffers from high path redundancy and poor smoothness, while the Dynamic Window Approach (DWA) tends to deviate from the global optimal path and has low efficiency in avoiding dynamic obstacles when integrated with global path planning. …”
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