Enhancing Real-Time Road Object Detection: The RD-YOLO Algorithm With Higher Precision and Efficiency by Weijian Wang, Wei Yu

“…Finally, we introduce MPDIoU as the new bounding box regression loss function, replacing the original loss function to accelerate algorithm convergence and improve target localization accuracy. …”
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Learning-Driven Algorithm With Dual Evolution Patterns for Solving Large-Scale Multiobjective Optimization Problems by Mingshuo Song, Wei Song, Khin Wee Lai

“…Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). …”
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Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm by Chunfeng Jiang, Zegang Niu, Jingru Qu, Yulan Zhao, Amin Rezaeipanah

“…Specifically, the proposed algorithm demonstrates a 9.2% improvement in average influence spread over the best existing method, while effectively addressing the trade-offs between influence, fairness, and complexity.…”
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Disease Detection Algorithm for Tea Health Protection Based on Improved Real-Time Detection Transformer by Zhijie Lin, Zilong Zhu, Lingling Guo, Jingjing Chen, Jiyi Wu

“…These findings indicate that the proposed algorithm is well-suited for efficient, real-time, and lightweight agricultural disease detection.…”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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A Hybrid Algorithm for PMLSM Force Ripple Suppression Based on Mechanism Model and Data Model by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. …”
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Optimizing Feature Selection and Machine Learning Algorithms for Early Detection of Prediabetes Risk: Comparative Study by Mahmoud B Almadhoun, MA Burhanuddin

“…PCA kept 12 components while maintaining 95% of the variance in the dataset. …”
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Automated Design Method Based on Boosting Algorithms for Improving the Radiation Performance of Microstrip Antenna Arrays by Sina Hasibi Taheri, Ali Lalbakhsh, Amirhassan Zareanborji, Slawomir Koziel

“…This reduces the number of trained networks while maintaining the prediction accuracy. Training networks for WAIM and antennas involve four different boosting algorithms: AdaBoost, Gradient Boosting (GB), Extreme Gradient Boosting (XGB), and Light Gradient Boosting (LightGB). …”
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A Comparative Analysis of Advanced Routing and Cluster Head Selection Algorithm Using Lagrange Interpolation by Zoren P. Mabunga, Jennifer C. Dela Cruz, Renato R. Maaliw

“…This paper presents a unified performance metric for evaluating the chronological wild geese optimization (CWGO) algorithm in wireless sensor networks (WSNs). The metric combines key performance factors—energy consumption, delay, distance, and trust—into a single measure using Lagrange interpolation, providing a more comprehensive assessment of WSN algorithms. …”
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ANALYSIS OF THE CHARACTERISTICS OF INTERNATIONAL STANDARD ALGORITHMS «LIGHTWEIGHT CRYPTOGRAPHY» – ISO/IEC 29192-3:2012 by A. S. Poljakov, V. E. Samsonov

“…The data on the characteristics of international standard algorithms «lightweight cryptography» while application in hardware implementation based on microchips of FPGA are provided. …”
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Prediction of Acute Kidney Injury for Critically Ill Cardiogenic Shock Patients with Machine Learning Algorithms by Zhang X, Xiong Y, Liu H, Liu Q, Chen S

“…Finally, we verified the prediction models using the data from our hospital and ensemble model still exhibited the best predictive ability (AUC:0.74, 95% CI, 0.62– 0.86), while the decision tree model obtained the worst predictive performance (AUC:0.52, 95% CI 0.35– 0.70).Conclusion: Machine learning algorithms could be utilized for the AKI prediction among critically ill CS patients, and exhibit superior predictive performance compared to the conventional logistic regression analysis.Keywords: cardiogenic shock, acute kidney injury, MIMIC database, prediction model, machine learning…”
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Optimising islanded AC microgrid control: A hierarchical approach with FCS-VMPC and consensus algorithm by Zawar Khan, Muhammad Aamir, Rizwanullah Khan, Mohd Fairouz Mohd Yousof

“…The primary layer is typically implemented using a linear controller, while the secondary control relies on complex control strategies. …”
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Innovative approaches to beam forming antenna array systems with adaptive Partial Update NLMS algorithms by Zahraa A. Shubber, Thamer M. Jamel, Ali.K. Nahar

“…In other hands, these PU algorithms maintain the radiation pattern with as little change from the original (distortion-free) as possible and symmetrical of the array, while. fewer elements are needed to produce the same amount of radiation. …”
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Mathematical Formulation of Intelligent Management Algorithms for Isolated Microgrids: A Pareto-Based Critical Approach by Vitor dos Santos Batista, Thiago Mota Soares, Maria Emília de Lima Tostes, Ubiratan Holanda Bezerra, Hugo Gonçalves Lott

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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
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GVDF-RRT*: An Improved F-RRT* Path Planning Algorithm Based on Generalized Voronoi Diagram by Yitao Zhong, Xiaojing Zhu, Jianfang Huang, Yaokun Ye, Zhaoming Wang, Yuhuai Wang

“…Finally, simulations in three test environments show that, compared to RRT*, Q-RRT*, and F-RRT*, the GVDF-RRT* algorithm reduces the initial number of sampled nodes by 47.42%-76.57%, the initial time by 37.07%-86.00%, and the initial path cost by 0.47%-0.91%, while significantly improving the success rate in narrow passage environments. …”
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Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

“…Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. …”
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Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines by L. A. Demidova, A. V. Gorchakov

“…The replacement of the iterative learning process currently used in many neural network architectures with the random initialization of input weights and the explicit computation of output weights significantly increases the performance of this novel machine learning algorithm while preserving good generalization performance. …”
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Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

“…As a combinatorial NP-hard problem, FS necessitates using powerful metaheuristic algorithms to serve as efficient wrapper-based FS strategies. …”
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Assessment of different genotyping markers and algorithms for distinguishing Plasmodium falciparum recrudescence from reinfection in Uganda by Alex Mwesigwa, Monica Golumbeanu, Sam Jones, Sara L. Cantoreggi, Benson Musinguzi, Joaniter I. Nankabirwa, Everd Maniple Bikaitwoha, Joan N Kalyango, Charles Karamagi, Mateusz Plucinski, Samuel L. Nsobya, Christian Nsanzabana, Pauline Byakika-Kibwika

“…The msp-1/msp-2/2490 combination identified more recrudescences using the ≥ 2/3 and 3/3 algorithms in the artemether-lumefantrine (AL) treatment arm, while msp-1/msp-2/glurp combination classified more cases of recrudescence using the ≥ 2/3 in the dihydroartemisinin-piperaquine (DP) arm. …”
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