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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Research on Underwater Sensor Network Adaptive Clustering Algorithm for Marine Environment Monitoring by Libin Xue, Chunjie Cao, Rongxin Zhu

“…The final calculated expected revenues are the user’s revenues after participating in the game under the influence of the multipath effect, and the revenues of all users jointly determine the performance of the clustering algorithm proposed in this paper. When the energy consumption of the CH node is too much and needs to be rotated, MEMAC, through a CH rotation mechanism and a comprehensive analysis of the overall remaining energy of the network, further optimizes the CH selection strategy while ensuring network stability. …”
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A Unified Multi-Target Clever Eye Algorithm: Analytical Solutions and Application by Lei Wang, Xiurui Geng, Luyan Ji

“…The clever eye (CE) algorithm has been introduced for target detection in remote sensing image processing. …”
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Decision tree-based machine learning algorithm for prediction of acute radiation esophagitis by Mostafa Alizade-Harakiyan, Amin Khodaei, Ali Yousefi, Hamed Zamani, Asghar Mesbahi

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Development of K-PANOSE Algorithm for Measuring and Classifying Shape Elements of Hangul Fonts by Soon-Bum Lim, Hyun-Young Kim, Kanghyeon Seo, Juhan Yoo, Yoojeong Song

“…We then designed an algorithm to quantitatively assess these attributes. …”
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Robust Adversarial Example Detection Algorithm Based on High-Level Feature Differences by Hua Mu, Chenggang Li, Anjie Peng, Yangyang Wang, Zhenyu Liang

“…By exploiting semantic conflicts in high-level features between clean and adversarial examples with the same predicted label, the method achieves high detection accuracy across diverse attack types while maintaining resilience to preprocessing, providing a valuable new perspective in the design of adversarial example detection algorithms.…”
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LE-YOLO: A Lightweight and Enhanced Algorithm for Detecting Surface Defects on Particleboard by Chao He, Yongkang Kang, Anning Ding, Wei Jia, Huaqiong Duo

“…Current algorithms for surface defect detection in particleboard often encounter limitations such as high computational complexity and excessive parameter scale. …”
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Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization by Idriss Dagal, AL-Wesabi Ibrahim, Ambe Harrison, Wulfran Fendzi Mbasso, Ahmad O. Hourani, Ievgen Zaitsev

“…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
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Optical detection of single and multiple seeding using an innovative shape-recognition algorithm by Ali Ghaffarnezhad, Hossein Navid, Hadi Karimi

“…In this research, a novel shape-based algorithm is presented that utilizes seven pairs of 3-mm infrared LEDs to efficiently recognize and count both single seeds and overlapping seeds. …”
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An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Compared to existing methods, the proposed approach maintains high detection performance while exhibiting significant computational efficiency advantages.…”
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Vehicle Authentication-Based Resilient Routing Algorithm With Dynamic Task Allocation for VANETs by Nagaraju Pacharla, K. Srinivasa Reddy

“…This research proposes a Vehicle Authentication based Resilient Routing Algorithm with Dynamic Task Allocation (VARRA-DTA) Scheme for selecting the optimal and secured route in VANET with effective task allocation strategy that reduces the latency in the network. …”
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ESPGD Algorithm to Improve the Convergence Speed for Adaptive Single-Mode Fiber Coupling by Jinjin Peng, Bo Qi, Yun Zhang, ZhenChuang Li, Yao Mao

“…The algorithm only needs to perform this process once in one iteration while the original SPGD algorithm needs to perform it twice to obtain the estimated gradient. …”
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RTL-Net: real-time lightweight Urban traffic object detection algorithm by Zhiqing Cui, Jiahao Yuan, Haibin Xu, Yamei Wei, Zhenglong Ding

“…Abstract Object detection algorithm in urban traffic using remote sensing images often suffers from high complexity, low real-time performance, and low accuracy. …”
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LSTM-DQN-APF Path Planning Algorithm Empowered by Twins in Complex Scenarios by Ying Lu, Xiaodan Wang, Yang Yang, Man Ding, Shaochun Qu, Yanfang Fu

“…This approach effectively enhances the diversity and accuracy of training samples while significantly reducing the experimental costs of the algorithm. …”
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Harmonic Measurement Algorithm of Power System Integrating Wavelet Transform and Deep Learning by Hanshu Jiang, Yutian Li, Zhu Liu, Guanghao Wu, Zeyang Liu

“…OBJECTIVES: The primary goal of this study is to develop a more accurate harmonic measurement algorithm by combining full phase fast Fourier transform (FFT) and adaptive neural networks. …”
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YOLO-v4 Small Object Detection Algorithm Fused With L-α by ZHANG Ning, YU Ming, REN Honge, AO Rui, ZHAO Long

“… The detection ability for small object is still need to be improved urgently in spite of the rapidly developing object detection technology based on deep learning at present.Compared with large objects, small object detection tasks hold drawbacks of low resolution and feature loss which leads to that many general algorithms cannot be directly applied to small object detection.The feature pyramid fusion can effectively combine the features of deep and shallow layers to enhance the performance.To solve the problem most models existing ignoring the imbalance of information during the feature fusion between adjacent layers, it is proposed to integrate the idea of fusion factor into the PANet of YOLOv4, use the fusion factor L-αto control the amount of information transmitted from the deep layer to the shallow, so as to effectively improve the efficiency of information fusion and enhance the ability of YOLO-v4 for small objects detection.With the addition of L-αin YOLO- V4 model, the experiment results show that the APtiny50and APsmall50on the TinyPerson are improved by 2.14% and 1.85% respectively, while the AP and APS on the MS COCO are separately increased by 1.4% and 2.7%.It is proved that this improved method is effective for small object detection with the evidence of better result than other small object detection algorithms.…”
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SACWOM: Synergistic Adaptive Congestion Window Optimization Mechanism for Self-Clocked Algorithm by Haider Dhia Zubaydi, Ahmed Samir Jagmagji, Sandor Molnar

“…Congestion Control (CC) is essential in networked systems, especially in environments with strict delay and throughput requirements. While CC algorithms like Self-Clocked Rate Adaptation for Multimedia (SCReAM) and Bottleneck Bandwidth and Round-trip propagation time (BBR) have shown progress, each faces limitations: BBR encounters difficulty in balancing responsiveness and fairness when rapid fluctuations in network conditions arise, which can lead to inefficient performance in shared environments. …”
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A Hybrid EV Charging Approach Based on MILP and a Genetic Algorithm by Syed Abdullah Al Nahid, Junjian Qi

“…This study underscores the potential of hybrid charging schemes in optimizing energy utilization while maintaining system reliability and user convenience.…”
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Acoustic impedance inversion via voting stacked regression (VStaR) algorithms by Lutfi Mulyadi Surachman, Sanlin I. Kaka, Abdullatif Al-Shuhail

“…To refine the AI estimation, we used stacking and voting regression algorithms, with depth, two-way travel time (TWTT), and nine seismic attributes as inputs. …”
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Comparative analysis of AI-based search algorithms in solving 8 puzzle problems by Ghaniyyat Bolanle Balogun, Daniel Ibisagba, Amos Bajeh, Taofik Olawale Debo, Abdulraheem Muyideen, Olumuyiwa James Peter

“…Abstract Background The 8-puzzle problem is a well-known combinatorial search problem, often used to test the effectiveness of various artificial intelligence (AI) algorithms. This study aims to evaluate the performance of three AI-based search algorithms—Breadth-First Search (BFS), Depth-First Search (DFS), and A* Search—in solving the 8-puzzle problem. …”
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