Opposition-based chaotic evolution for optimization by Tianshui Li, Yan Pei

“…Abstract Evolutionary computation algorithms are widely used for solving complex optimization problems, but their practical performance is often hindered by high computational costs and premature convergence. …”
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Transactive energy management for efficient scheduling and storage utilization in a grid-connected renewable energy-based microgrid by Peter Anuoluwapo Gbadega, Olufunke Abolaji Balogun

“…This study presents an advanced Transactive Energy Management (TEM) approach employing the Slime Mould Algorithm (SMA) to optimize scheduling and storage utilization in grid-connected renewable energy microgrids. …”
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A Ship’s Maritime Critical Target Identification Method Based on Lightweight and Triple Attention Mechanisms by Pu Wang, Shenhua Yang, Guoquan Chen, Weijun Wang, Zeyang Huang, Yuanliang Jiang

“…To verify the effectiveness of these algorithmic improvements, the DTI-YOLO algorithm was tested on a self-made dataset of 2300 ship navigation images. …”
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An algorithm for heterogeneous wireless network connections for user preferences and services by S. Dinesh Krishnan, A. Daniel, S. Ayyasamy, Balamurugan Balusamy, Shitharth Selvarajan, Taher Al-Shehari, Nasser A. Alsadhan

“…Abstract Heterogeneous wireless networks (HWNs) present a challenge in selecting the optimal network for user devices due to the overlapping availability of multiple networks. …”
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Detection of Welding Defects Using the YOLOv8-ELA Algorithm by Yunxia Chen, Yangkai He, Lei Wu

“…The model integrates a novel HS-FPN feature fusion module, which optimizes the parameter efficiency and enhances the detection performance. …”
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Research on Control Method of Electron Accelerator Based on Simulink Simulation by YUE Hongwei1, LI Zhongping2, 3, ZHOU Youwei2, CAO Shuchun2, 3, REN Jieru1, ZHANG Zimin2, 3, , ZHAO Yongtao1

“…The three algorithms were subsequently applied to this mathematical simulation model within MATLAB’s Simulink environment. …”

User preference information recommendation based on DCGNN and GNNPK algorithms by Nannan Cheng, Xiaoyang He

“…Especially when dealing with challenges such as user dynamic preferences, data noise, and cold start, the limitations of these systems become increasingly obvious, and more advanced algorithms are urgently needed to improve the personalization and accuracy of recommendations. …”
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Topology Knapsack Problem for Geometry Optimization by Hsiao-Hui Li, Po-Chun Chang, Yuan-Hsun Liao

“…While several variants have been developed, including the 0/1, fractional, and multi-dimensional knapsack problems, no existing model simultaneously optimizes multiple attributes like rarity, importance, and preference alongside the weight and volume of items. …”
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Engineering Quantum Error Correction Codes Using Evolutionary Algorithms by Mark A. Webster, Dan E. Browne

“…Finally, we show that the algorithm can be used to optimize stabilizer codes for biased error models, demonstrating a significant improvement in the undetectable error rate for <inline-formula><tex-math notation="LaTeX">$[[12,1]]_{2}$</tex-math></inline-formula> codes versus the best-known-distance code with the same parameters. …”
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Application of the Random Forest Algorithm for Accurate Bipolar Disorder Classification by Miguel Suárez, Ana M. Torres, Pilar Blasco-Segura, Jorge Mateo

“…Its ability to reduce diagnostic delays, improve classification accuracy, and optimize resource allocation make it a promising tool for integrating artificial intelligence into psychiatric care. …”
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Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…In response to this problem, this paper proposes a robust UAV target tracking algorithm based on saliency detection (SDBCF). Using saliency detection methods, the DCF tracker is optimized in three aspects to enhance the robustness of the tracker in complex scenes: feature fusion, filter-model construct, and scale-estimation methods improve. …”
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Deloading Algorithm for Highly Effective Suppressing Locomotive Slip and Slide by LI Jianghong, CHEN Huaguo, HU Zhaowen, XU Li, PENG Huishui

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Machine Learning-Based Lithium Battery State of Health Prediction Research by Kun Li, Xinling Chen

“…The PSO algorithm was employed to optimize model parameters, resulting in the construction of three predictive models: PSO-LSTM, PSO-CNN, and PSO-SVR. …”
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Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm by Gao Chaomeng, Wang Yonggang

“…Finally, the collaborative filtering algorithm is optimized to improve the consumer similarity based on the original algorithm. …”
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Retracted: Research on GNSS-Assisted Low-Cost INS Combined Navigation Moving Base Initial Alignment Technique by Mengbo Sun, Jian Huang, Pengcheng Hu, Xiaohui Song, Zhu Li

“…The measured results show that the proposed method has better alignment accuracy and algorithm robustness than the existing Optimization-based alignment and their improvement algorithms for the moving base of low-cost INS/GNSS combined navigation.…”
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Overcoming Data Scarcity in Calibrating SUMO Scenarios With Evolutionary Algorithms by Jakob Kappenberger, Heiner Stuckenschmidt

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YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…This paper presents YOLO-Dynamic, a novel detection algorithm aimed at addressing the limitations of existing models, particularly in complex environments and small-object detection. …”
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Real-Time Estimation of the State of Charge of Lithium Batteries Under a Wide Temperature Range by Da Li, Lu Liu, Chuanxu Yue, Xiaojin Gao, Yunhai Zhu

“…The results indicate that creating a database that accommodates temperature variations and optimizing dual Kalman filtering through the cat swarm optimization algorithm significantly improves <i>SOC</i> estimation accuracy.…”
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Multi-Feature Facial Complexion Classification Algorithms Based on CNN by Xiyuan Cao, Delong Zhang, Chunyang Jin, Zhidong Zhang, Chenyang Xue

“…The optimal approach combining multi-feature CNN with machine learning algorithms attains a remarkable accuracy of 97.78%. …”
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Surrogate-guided optimization in quantum networks by Luise Prielinger, Álvaro G. Iñesta, Gayane Vardoyan

“…Our algorithm consistently outperforms Simulated Annealing and Bayesian optimization within the allotted time, improving results by up to 29% and 28%, respectively. …”
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